CAMBRIDGE TALENT STUDY - Amazon S3...CAMBRIDGE TALENT STUDY Talent Stack of the Job Families...

1

CAMBRIDGE TALENT STUDY

DECEMBER 2018

2

AGENDA

CAMBRIDGE TALENT STUDY

Talent Stack of the Job Families analysed, Job role/Skill level analysis

Industry Level Analysis : Top peer employers, workloads, talent maturity analysis and salary distribution

Start-up Deep Dive: Analysis of Funding, Acquisitions and top start-ups across technology areas

University Analysis: Talent supply analysis, Professors profiling

Overview of the Cambridge ecosystem

Major Talent Hotspots : Hotspots of peer employers

Career Progression analysis: analysis of adjacent talent and Demand supply gap analysis

2

3

Executive Summary (1/3)

- Technology companies are embracing the concept of “Micro hubs” wherein they take advantage of talent across the globe, even if it is in

smaller numbers in some instances. There are several examples of “Micro hubs” in Cambridge, UK including companies like Microsoft,

Samsung and Apple.

- It is at this juncture Draup studied Cambridge, a diverse ecosystem offering wide range of possibilities across different fields. A mix of Hi-

tech, Healthcare and University talent has contributed tremendously to the evolution of Cambridge

- The uniqueness of this study is the depth of talent analysis done across industries, peer companies, technologies, job families and skills.

We believe that this will provide us an overall view of the state of the talent both on the supply and demand side.

- Our methodology included detailed analysis of open job descriptions across the last 3 to 5 years and develop a consolidated job corpus

data for mining purposes. Further to this analysis, we conducted multiple interviews and discussion sessions to understand the current

economic rationale of Cambridge, emerging technologies, talent spread and potential unicorns.

- The roles across the job corpus were organized into 8 roles – AI/ML, NLP, Computer Vision, Security, S/W Development, UX/UI, Cloud

and IoT/Hardware. This is essential for us to triangulate a huge data corpus to a reasonable number of dimensions in order gain deeper

insights.

- Cambridge, also known as “Silicon Fen” is organized as multiple clusters

- North Cambridge - Hotspot for Software/Internet, Semiconductor and Life Science Employers. It has Cambridge Science Park

and St. John’s Innovation Park

- South Cambridge - Healthcare and Life science Hotspot. It has Cambridge Biomedical Campus, hub for ~34 biomedical firms

- West Cambridge – Academia. University of Cambridge is located here.

- East Cambridge – Non knowledge intensive businesses e.g.- manufacturing and production industries

3

4


- Our analysis shows the total workforce of Cambridge is ~110,000 in 2017. Out of which 86,000 talent has been mapped across non-

IT(68,000) and digital(18,000) job families. Academic and Medical professionals employ ~50% of the non-IT talent where as Software

Development and IT Infrastructure employ ~48% of the digital talent.

- Algorithms, Data Science and Deep learning are the top skills in AI/ML Job family; Cloud Computing, Network security & management,

Ruby and Information security are the top 4 skills across Cloud and Security Job families.

- Job Demand : S/W Development and AI/ML are the top job families with most open positions, cumulatively contributing to ~62% of total

demand across ~3400 Job openings. Enterprises in Software/Internet and Healthcare industries, hired the largest talent pool across

AI/ML, Security and UX/UI Job families over the past 6 months.

- Salary Analysis : Computer Vision and NLP are the highest paid professionals across all job roles analysed.

- Installed talent distribution and technology focus across top 3 industries :

- Enterprise/Software : Software Engineers constitute 60% of the total digital talent. Predictive Analytics, Human computer interaction

and 3D Modelling/Mapping are the major focus areas in AI/ML

- Hardware/Semiconductor : IoT Engineers constitute 47% of the total digital talent. Embedded System Software and Autonomous

Driving are the major focus areas across IOT

- Life Sciences : Software Engineers constitute 37% of the total digital talent. Health Data Analytics, Gene Sequencing and Chronic

Rare Diseases Management are the emerging capabilities in health care with high AI/ML innovation

4

5


- Cambridge is home to ~210 start-ups which has seen a 30% YoY growth with a cumulative funding of ~$1 Bn; ~47% of the funding in

2017 was received by Healthcare sector, followed by Software/Internet (38%).

- Tech giants have made landmark acquisitions from companies spun out from University of Cambridge. Major acquisitions have happened

around ML/NLP/Computer Vision and Security segments.

- Considering the talent supply, a detailed analysis of over 6 premium universities in Cambridgeshire showed that the fresh

Software/Computer graduates were around 900.

- The universities in Cambridge are responding well to the changing demand of tech companies by introducing niche courses in computer

vision, natural language processing, neural computing, network simulation and modelling etc., compared to the rest of the world

universities.

- Top tech companies have predominantly collaborated with University of Cambridge for co-innovation, skill – enhancement and setting up

of digital labs/research centers.

- Upskilling the existing technical workforce into advanced Data Science/AI/Cloud/Security roles is being done through certifications

provided by universities and top tech companies. Apart from University of Cambridge, this is currently accomplished through partnerships

with training institutes such as Cambridge Spark and online platforms such as Khan Academy and Coursera.

- We have also conducted deep analysis across different technology segments

- The type of products, partnerships, acquisitions, collaborations and scholarships by big companies - Hiring Difficulty analysis

5

6

CAMBRIDGE - OVERVIEW

Cambridge is the fastest growing economy in the

UK with an annual year-on-year growth rate of

~2.2%. While the employment rate has increased

by 0.8% during 2017-18

In this report, DRAUP has analysed the Cambridge talent

ecosystem comprising of Top enterprises, Startups and

Universities

1

~110,000Total Employment (2017)

Insights

2

3

4

About this report

~11,700Total Employers

~18,000*Digital and IT Talent

1Cambridge cluster generates 12.3 Billion Euro which constitutes ~4% of the UK GDP. The cluster

employs ~110,000 workforce spread across 11,700 companies.

1Cambridge has ~18,000 digital talent pool which is largely employed across Software/Internet,

Semiconductor, Biotech enterprises and ~1200 mid scale organizations and start-ups

1Nearly ~13,500 talent is employed across 7 digital technologies – IOT, AI/ML, Cloud, Software

Development, Security, Analytics and UI/UX design

~900 Software students graduate from University of Cambridge and Anglia Ruskin University. Top

Golden triangle universities i.e. Imperial collage London, Oxford university and University Collage

London supply a large talent pool

Note: The represented data has been analysed using DRAUP Proprietary Talent Database 6

7

Cambridge has a total workforce of ~110,000, majority of which is employed in Education, Human Health & Social, and Professional Scientific & technical sectors

Source: DRAUP talent module was leveraged to analyze employment across industries

Unemployment rate* ~2.73%

Median age ~30 Years

Sex ratio 48 Female/52 Male

GDP ~$10.64Bn

GDP growth rate 2.19%

Median Household Income $65,660

Percentage of workforce across different industries

Total Workforce : ~110,000Cambridge is the 3rd largest Healthcare cluster in the worlds

after Boston and San Diego

32 Colleges and Research Institutions in Cambridge employ

~21% of the overall talent

Cambridge Science park is the hub for Hi-tech companies

Manufacturing construction and utility companies employ

5% of the total employed talent

Population: ~1,24,900

Non-Cambridge

Workforce*:~38.6%

Top Spoken Languages: English, Spanish, French, Chinese,

Ethnicity: White British(73.5%)

7

8

8

Silicon Valley of the UK, dubbed as “Silicon Fen”, is broadly clustered into Hi-tech(North), Life science(South), Academia(West) and non-knowledge intensive businesses(East)

Hotspot

Enterprise/Software

Companies

Semiconductor/Telecom

munication Companies

Pharma & Healthcare

Companies

Tech Giants

INDEX

Redgate

Software

Cambridge Wireless

NORTH CAMBRIDGEHotspot for Software/Internet, Semiconductor and Life Science

Cambridge Science Park, St John’s Innovation Park TOP COMPANIES – Beyond Media Limited, GW Pharmaceuticals

Major life science companies are moving towards South since

South Cambridge is an active Healthcare innovation hub

WEST CAMBRIDGEACADEMIA – University of Cambridge

UC is relocating its Engineering, CS and AI/ML departments to the vicinity of tech companies

SOUTH CAMBRIDGE

Healthcare and Life science Innovation HotspotCambridge Biomedical Campus (34 Biomedical Companies)

TOP COMPANIES – AstraZeneca, GlaxoSmithKline, Abcam

EAST CAMBRIDGE

Non-knowledge intensive businesses Manufacturing and Production industries are consolidated in Eastern Cambridge

IBM

AVEVA Audio Analytic

Cycle

Pharmaceuticals

GW

Pharmaceuticals

Napp Pharmaceutical

Group Ltd

Citrix

Cambridge

Apple Siri R&D Centre

Samsung R&D

Centre

Microsoft R&D

Centre

AstraZeneca

Qualcomm

Toshiba

Illumina

GSK

Broadcom

Philips

Healthcare

Darktrace

Cambridge Intelligence

Amgen LimitedMyrtle Software

Cambridge Biomedical Campus

Cambridge Science Park

St John’s Innovation Park

Universities

University of

Cambridge

Anglia Ruskin

University

Huawei

Abcam

AstraZeneca

Cancer ResearchAdenbrooke’s

HospitalARMS

Holding

Note : DRAUP’s proprietary talent module was used to analyse hotspots by locations and Industry wise

9

Employment opportunities, low cost of living and extensive research ecosystem attracts talent towards Cambridge

Cambridge

London

Oxford

Non-Resident Commuters

Cambridge has high in-commuting workforce, constituting ~35% of the overall

employment; Majority of commuters are from Cambridgeshire~38,500In-Commuters

Seamless Connectivity

The average journey time between Cambridge-London and Cambridge-Oxford is ~1

hour. There are 184 trains per day travelling from London to Cambridge~1 hr

Commute time

“Golden Triangle” - Global Research Hub

Cambridge is known as Silicon Fen with strong university background in bioscience and

software, golden triangle has a total of ~22,700 resident graduates~22,700Graduates

Relatively low Cost of Living

~12% Lower cost of living than that of London; 20% lower Housing cost in Cambridge

compared to London~12%

Lower Cost of living wrt UK

High Paying Jobs

Cambridge’s average salary is £35,900, which is ~32% higher than the national average~32%Higher than national avg

University of Oxford

University Collage London & Imperial Collage London

University of Cambridge

Note : DRAUP’s proprietary talent module was used to analyse the talent attraction towards Cambridge 9

10

Non-IT Job Families: Academics and Medical Professionals employ ~50% of the non-IT talent

Employed Talent in Non-IT Job families

~6600

~23000

~7000

~4000

~900~2500 ~1700

~11000

~1700 ~2500 ~2000

~5000

Core Engineering

Academics Operations Sales FinanceMedia &

Communication

MarketingMedical

ProfessionalsHuman

ResourcesArts & Design

Social Service

Consulting & Business

Development

Total Talent : ~68,000

Mechanical Engineer

Telecom Engineer

Civil Engineer

CAD Engineer

Professor

Counsellor

Curriculum Developer

Assessment Associate

Line Supervisor

Purchase Specialist

Supply Chain Analyst

Production Manager

Sales Representative

Account Executive

Business Developer

Sales Analyst

Financial Analyst

Trader

Quantitative Analyst

Portfolio Manager

Media Planner

Social Media Manager

Public Relations

Officer

Web ContentManager

Content Strategist

Marketing Data Analyst

Digital Brand Manager

SEO Specialist

Medical Assistant

Doctor

Pharmacist

Dietitian

Recruiter

Labour Relations Specialist

Compensation Analyst

Training Manager

Animation Expert

Advertising Specialist

Architect

Fashion Designer

Social care manager

Community Worker

Psychiatric Social Worker

House Manager

Client Retention Manager

Executive coach

Strategy Consultant

Digital Transformation

Expert

Note: The represented data has been derived using DRAUP Proprietary Talent Database 10

11

Digital Job families: Software Development and IT Infrastructure employ ~48% of the total talent

IT Infrastructure

TestingIoT/Embedded

/HardwareCloud

Analytics/BI

Software/Web/Mobile Development

Data Science/ ML

UI/UX DesignSecurity

900 500 1,700 5,300

2,600

600 2,000

1,100 3,300

Employed Talent

Total Talent across 9 tech job families: ~18,000

Employed talent in Digital and IT Jobs across 9 Job Families

Security Engineer

Penetration Tester

Incident Handler

Security Analyst

UX Designer

UX Researcher

UI Developer

Interaction Designer

Data Scientist

ML Engineer

Applied Scientist

Interaction Designer

Software Engineer

Full stack developer

Web Developer

IOS Developer

Data Analyst

Risk Analyst

Visualization Analyst

BI Analyst

Cloud Engineer

Cloud Enterprise Architect

Cloud Applications Engineer

Cloud Infrastructure Engineer

Embedded Software Engineer

Firmware Engineer

Compiler Engineer

IoT Developer

Test Engineer

SDE in Test

Test Automation Engineer

IT Test Analyst

Infrastructure Engineer

IT Infrastructure Developer

Systems Engineer

Network Engineer

Note: The represented data has been derived using DRAUP Proprietary Talent Database 11

12

Top Skills: Large proportion of employed talent pool is skilled in programming languages such as C/C++, Python and SQL

J2EE 200 Hadoop 200 Swift 180 Ruby on Rails 160 Chef 150

C/C++ 7,000 Python 3,700 SQL 3,500 Java 3,100 MATLAB 2,800

Perl 1,400 Git 1,300 .NET 1,150 Shell 1,000 jQuery 900

Open Source 850 Shell Scripting 700 Eclipse 550 DNS 500 Jenkins 400

Bayesian 400 Ruby 350 Node.js 300 Deep Learning 270 SAS 250

HTML 2,600 JavaScript 2,250 Machine Learning 1,600 XML 1,500 PHP 1,450

Hig

hM

ediu

mLo

w


13

Top Skills - AI/ML- Algorithms, Data Science and Deep learning are the top skills in AI/ML Job family

AI COMPUTER VISION NLP

550500

1350

1600

850

150100

900

200150

100

StatisticalModelling

PredictiveModelling

Data Science Algorithms Image Processing OpenCV Machine Vision Deep Learning SpeechRecognition

Text Mining ComputationalLinguistics

Statistical Modelling

Predictive Modelling

Deep Learning

Image Processing

OpenCVMachine

VisionText Mining

Computational Linguistics

Speech Recognition

AlgorithmsData

Science


14

Top Skills - Cloud and Security: Cloud Computing, Network security & management, Ruby and Information security are the top 4 skills across Cloud and Security Job families

550

270

230

300

170140

180

350

530

350

150

Cloud Computing Virtualization ITIL Firewall VPN TCP/IP JSP/J2EE Ruby Network Security& Management

InformationSecurity &

Management

ISO27001

SECURITY

JSP/J2EE Ruby

Network

Security &

Management

Information

Security &

management

ISO27001Cloud

ComputingVirtualization ITIL

CLOUD INFRASTRUCTURE

Firewall TCP/IP VPN

CLOUD SECURITY CLOUD APPLICATION


Digital Job Demand: Cambridge has a total Digital demand of ~3400; S/W Development and AI are the top Job families contributing to ~62% of total demand; Time to hire is highest for Computer Vision

Key Job Roles Open PositionsTime to Hire

(Days)Key Job Titles Key Employers

AI /ML ~620 ~45Machine Learning Engineer, Machine Learning Specialist, Deep Learning Engineer, Machine Learning Platform Engineer

Amazon, Apple, Arm, Microsoft, Prowler.io

NLP ~50 ~40Applied Scientist, NLP Engineer, NLP Research Scientist, Language Engineer

Amazon, Apple, Huawei, Harnham

Computer Vision ~100 ~60

Computer Vision Engineer, Computer Vision Scientist, Applied Computer Vision Scientist, Software Engineer (Computer Vision), Computer Vision Research Engineer

Amazon, Arm, Huawei, Microsoft, Nvidia

Security ~100 ~40Information Security Manager, Information Security Engineer, Cyber Security Engineer

Amazon, Arm, AstraZeneca, Genomics, Google, Microsoft

S/W Development ~1500 ~30Software Developer, Android Software Developer, Application Developer, Front End Developer

Amazon, Arm, Citrix, Microsoft, Qualcomm

UX ~200 ~25UX/ UI Designer, UX Architect, UI Software Engineer, UX Researcher, UI Developer

Amazon, Arm, Microsoft, Redgate, Lucidworks

Cloud Engineer ~500 ~40Cloud Architect, Cloud Software Development Engineer, Cloud Systems Engineer, Cloud Devops Engineer

Citrix, Genomics, Microsoft, Prowler.io, Nokia, Qualcomm

IoT ~350 ~45IoT Test Automation Engineer, IoT Software Engineer, System Test Engineer (IoT)

Arm, Nokia, Qualcomm

Note: Data Science is considered in AI/ ML job role 15

16

Recent Hiring Analysis*: Enterprises in Software/Internet and Healthcare industries hired the largest talent pool across AI/ML, Security and UX/UI Job families over the past 6 months

AI/ ML NLPCOMPUTER

VISIONSECURITY

S/W

DEVELOPMEN

T

UI/UXCLOUD

ENGINEER

IOT

EMBEDDED

Software Internet

Healthcare/

Biotechnology

BFSI

Automotive

Telecommunicati

on

Electronics/Semi

conductor

Top Employers

Microsoft, Oracle

AstraZeneca, Sogeti, 10x Genomics

Citi, HSBC, UBS, Bank of England

Jaguar Land Rover, Vindis Group

Huawei, Virgin Media Business

Arm, Qualcomm, Citrix

Low Medium High

Total 1,300 professionals hired for following new age job roles across different industries across past 6b months

0 400Talent size

Note : DRAUP’s proprietary talent module was used to analyse technology talent across different Industries. The Talent count is inclusive of Applied Scientist counts in each of the domains 16

Cost Analysis: High demand for Data science and Software developer talent is driving the high Salary for these Job roles

Note : DRAUP’s Talent Simulation Module

Med

ian

Sa

lary

(U

SD)

per

an

nu

m

£40,000

£30,000

£35,000 £35,000£33,000

£30,000

£45,000 £45,000

£52,000

£45,000£42,000

£47,000

£42,000 £41,000

£55,000£58,000

£70,000

£60,000

£70,000

£65,000

£55,000 £55,000

£75,000£78,000

Data Science Software Cloud Security UI/UX Design IoT Computer Vision NLP

Entry (0-5) Middle(5-10) Senior (10+)

£42,000 £58,000 £60,000£54,000 £45,000 £49,000 £49,000 £43,000

XX,XXXAverage Salary

Note : DRAUP’s Talent Simulation Module17

18

Digital Talent Distribution: 72% of the Digital talent is employed by Enterprises; Software internet, Semiconductor and Healthcare are the major industries constituting 86% of the installed talent

53%

20%

13%

<5% <5%<10%

Software/ Internet Semiconductor Healthcare Telecom Financial Services Others

Total Digital and IT Talent

~5000

Total Digital and IT talent across Enterprises :

~ 13,000

Top Employers Top Employers

Enterprises1 Start-ups2

Note: Others include talent from industries like Electrical Engineering, Mechanical Engineering, Aviation etc. 18

Enterprise Analysis

19

Top Employers by Job Openings: AstraZeneca, ARM, Microsoft and Qualcomm have the highest job openings for Data Scientist, AI/ML and software development roles

Peer

Employers

Open

Jobs

Data Science

/ML/AISecurity

Software

DevelopmentUI/UX Cloud

IoT/

EmbeddedAnalytics/BI Centre Product Focus

~40

ML Engineer,

Knowledge

Engineer, Data

Scientist

UX Designer/

Researcher

Data & Analytics

Engineer,

Genomics D&A

Engineer

ONCOLOGY

BIOINFORMATICS, OPTIMIZE

CLINICAL DEVELOPMENT

PROGRAMS

~100

Principal Security

Architect, Security

Researcher,

Information

Security Risk

Engagement

Manage

Solution Architect,

Software Engineer,

Lead Java Web

Developer

UX Designer

Firmware

Development

Lead, Compiler

Engineer, Software

Engineer-

Prototyping,

Design Engineer

Software Engineer,

Engineering

Analytics

ENGINEERING ANALYTICS

TEAM, SECURITY RISK

MANAGEMENT AND

COMPLIANCE (SRMC) TEAM

~45

Data Scientist,

ML/AI Engineer,

Software Engineer

Machine Learning,

Deep Learning

Researcher

Security Research

Software Engineer

Software

Development

Engineer

Web Development,

UX Design

Cloud Software

Engineer

Graduate

Hardware

Engineer

FEMTOSECOND LASERS TO

STORE DATA IN GLASS, MS

EXCEL, CONFIDENTIAL

COMPUTING, HEALTHCARE AI

PRODUCTS

~10

Senior Software

Engineer, IT

Engineer,

Software Product

Manager

Application

Engineer,

Engineering

Technician, RF

systems Engineer

CDMA TECHNOLOGY, DIGITAL

DESIGN TEAM, RF SYSTEMS

TEAM

Open Job Area Intensity High Low

Note : DRAUP’s proprietary talent module was used to analyse peer employers by skill type 20

21

21

Strategic focus : Tech giants, Semiconductor and Life sciences companies have technology focused teams in Cambridge;

Pharma/Biotech firms in Cambridge are focusing on Bioinformatics and Genomics

Life Sciences & Biotech start-ups have received ~$470 M funding, highest among all industries

Semiconductor firms are leveraging Cambridge to build end-to-end IoT capabilities

Tech Giants have set up Cambridge Centres for it’s high quality research in Artificial Intelligence/ ML/ Computer Vision/NLP

Software/Internet

Semiconductor Scaled Startups

Acquired Cambridge Silicon Radio (CSR), The acquisition complements Qualcomm's current offerings by adding products, channels, and customers in the growth categories of Internet of Everything (IoE) and automotive infotainment.

Pharmaceutical / Biotech

Acquired VocalIQ, which uses ML, NLP to build virtual assistant, the product was integrated into Siri. Apple has used the acquisition as a base to expand it’s presence

Set up an AI-research centre in Cambridge. Major focus on Computer Vision and ML. Working on Automatic Human Behaviour Analysis.

Set up it’s research centre in 1997, and has since scaled to 130+ researchers and engineers working across data centres, cloud and healthcare

ARM acquired Silicon valley based Treasure data, an enterprise data management company to build a device-to-data IoT platform Pelion. It’s earlier acquisition of Stream for connectivity management, allows it to offer devices management, connectivity management and data management in it’s platform , complementing it’s IoT hardware capabilities

Mission Therapeutics has raised ~$127m for it’s drug discovery and development platform

Crescendo Biologics has raised ~$116m. It is a biopharmaceutical company developing potent, truly differentiated Humabody® therapeutics in oncology with a focus on innovative targeted T-cell approaches.

Bicycle therapeutics has raised ~$90m,it’s a biotechnology company pioneering a new class of therapeutics based on its proprietary bicyclic peptide (Bicycle®) product platform, with a major focus on Oncology

Collaborated with Cancer Research UK to setup a Functional Genomics Centre, work on genetic screening, cancer modelling and big data processing aimed at accelerating the discovery of new cancer medicines

Collaborated with California-based Innovative Genomics Institute (IGI) to use CRISPR to uncover genes and disease pathway mechanisms involved in DNA Damage Response (DDR)

Astrazeneca has adopted the Horizon Discovery’s Edit-R™ crRNA libraries as part of a drive to establish a functional genomics discovery platform.

Note : DRAUP’s proprietary talent module was used to analyse strategic focus across different Industries

22

22

Software/Internet - Tech Giants Team Structure:Tech giants have hired University professors and leaders from peers for leading their product teams

Talent Distribution

~ 20%

~ 60%

~ 20%

Total R&D Size in Cambridge

ResearcherCTO, (Hypertag)PhD, University of Cambridge

Previous Experience

Hiring

Focus from

PRODUCT LEADERSHIP

MID LEVEL ROLES

Chief Research Scientist

Software Development

Engineer

Technical Support Engineer

Staff Engineer

Speech and Machine Learning

Research Scientist

Machine Learning Engineer

Partner Scientist

Principal Scientist

~10-12Average Product

Team Size

Principal Software Engineer

Principal Architect

Product Team Structure~30 ~40 ~100

Un

ive

rsit

y

Sta

rt-U

ps

Pe

ers

Chief Research ScientistProfessor of Computer Science (University of Edinburgh, Aston University)

Senior ScientistResearch Director (University of Cambridge)

Partner ScientistPhD, AI (University of Edinburgh)

Data and Applied ScientistLanguage Processing Engineer, (Swiftkey)Mphil (University of Cambridge)

Principal Applied ScientistSenior Researcher, (Fraunhofer-FIRST)

ML EngineerStatistician (deCODE genetics)

Machine Learning EngineerMphil, ML,Speech & Language Technology (University of Cambridge)

Speech and Machine Learning

Research ScientistSenior NLP Researcher (VocalIQ)

ML EngineerDeep Learning Research Engineer, (Smart Eye)

Technical Program Manager - SiriWeb and Mobile Development, (HP)

NLP Dialogue EngineerPhD in Computer Science(University of Cambridge)

Software Engineer

Software Engineer (Google)

ENTRY LEVEL ROLES

Chairman Samsung AI ResearchProfessor, Machine Intelligence (University of Cambridge)

Program Director, Samsung AIPrincipal Scientist, (Nokia Bell Labs)

System Team Lead Principal Engineer, (CSR)

Principal NL Research Engineer(Nuance Communications)

Senior Engineer -SAICPrincipal NL Research Engineer(Nuance Communications)

Senior Researcher -SAICResearch Scientist (Nokia Bell Labs)

Hired from Start-UpsHired from University Hired from PeersLegend:

Note : DRAUP’s proprietary talent module was used to analyse product team structure of tech giants

23

Software/Internet: Software developer Job family constitutes majority of the employed digital talent; Tech Giants have high focus on AI/ML and NLP

100 - 120

Focus Areas: Hybrid Cloud Application, Multi-Cloud

networking, analytics intelligence with machine learning,

Virtualization technologies

30 - 40

Focus Areas: Game Design , Game Mechanics ,

Console Development, Build and support game

systems, work with COBRA engine, Graphic Design

150 -200

Focus Areas: Biological Computing, Human Experience

& Design, Machine Intelligence and Perception

Project Emma - Help Person suffering from Parkinson’s.

Project Torino - physical programming language for

children with vision impairments

250- 300

Focus Areas: MATLAB, Simulink product

development and support, Automatic Code

Generation, Deep Learning Development

130-150

Focus Areas: Natural Language Processing,

Automotive Voice Recognition, Speech Recognition

Siri - Integrate machine learning models with Siri’s

Architecture

Products/Technologies

20%

AI/ML CloudSoftware

DeveloperSecurity UI/UX IoTNLP

15%

0%

5% 5%

5%

0%

10%30%

40%

50%

50%

10% 0% 0%50%

10%

5%

0%

30% 0%

5% 0%

10% 0%

0%

0%

5% 5% 5%

0% 25%

0%20%

10%

0% 0-25% 25%-50%

Note : DRAUP’s proprietary talent module was used to analyse jobs by top companies and skill type 23

24

Software/Internet: Talent Maturity Analysis - Over 65% of the employed digital talent in Security and IOT Job families have 10+ years of experience

35%

24%

13%8%

31%

15%

45%53%

22%

21%

33%

17%

25%

20%

22%

20%

43%

55% 53%

75%

44%

65%

33%27%

Data Science Software Engineer Cloud Security UI/UX IoT Computer Vision NLP

0-5 Years 5-10 Years 10+ Years

Employed Talent Distribution Across Job Roles and Years of Experience

~650 ~2,600 ~300 ~300 ~280 ~200 ~250 ~100

Enterprise/Software Talent~4,300

Employed Talent is

(analyzed job roles)

Note: Talent size for NLP and computer are included in Data Science Job family

Embedded Job roles are included in analysis of IOT Job family


25

Software/Internet : Technology Focus - Predictive Analytics, Human computer interaction and 3D Modelling/Mapping are the major focus areas in AI/ML

Mid scale software companies are developing Behavioural Learning, Analytics and simulation technologies for Virtual environments. FiveAIis leading the development of Autonomous Driving software systems in Cambridge Area

Citrix is Developing new security analytics service to combat insider security threats and detect malicious activities using data from Citrix systems such as NetScaler MAS, OctobluIoT

Microsoft is developing AI-based Navigation and Positioning systems, also researching on Human Interaction and Biological Computation

AI/ML, Computer Vision, Natural language Processing and Cybersecurity are key focus areas for Software/Internet companies in Cambridge

INSIGHTS

Major technology companies like Apple and Amazon have set-up small-scale teams for research and development of Automatic Speech Recognition & Language Translationfor Siri and Alexa Products.

Hiring Matrix

Function of the number of Current Job Openings and

Last 1 year hiring as percentage of Employed talent

Talent Maturity

Function of employed talent pool size

Low

High

Em

plo

ye

d T

ale

nt

Po

ol

Ind

ex

High

Predictive

Analytics

Cybersecurity

Human-

Computer

Interaction

Biological

Computation

Behavioural

Learning &

Simulation

Navigation &

Positioning

Automatic

Speech

Recognition

Chatbots

Language

Translation

Natural

Language

Understanding

Real-time

Threat

Monitoring Autonomous

Threat

Response

Cloud

Security

Object

Identification

& Tracking

3D Mapping

3D Modelling

Visual Text-

to-Speech

Game

Development

Enterprise

Applications

Systems

Software

Mobile

Applications

Data

Visualisation

Softwares

Hiring Matrix

Nascent CapabilitiesNiche Capabilities

Emerging CapabilitiesMature Capabilities

Sound

Recognition

Autonomous

Vehicles

Image

Enhancement

S/W Dev.

Security

AI/ML

Cloud

Computer

Vision

IoT

UI/UX

Design

NLP

Note: The above analysis is based on the DRAUP’s proprietary engineering database25

26

Semiconductor Industry : Software developer Job family constitutes majority of the employed digital talent; ARM, Qualcomm and Samsung also have high focus on IOT

Products/TechnologiesAI/MLComputer

Vision

Software

DeveloperSecurity UI/UXNLP

IoT/Embe

dded

400-450Primary focus is on pioneering IoT and automotive

technologies, with engineering areas like Analogue and

Digital Design, Voice and Music (Hardware, Software, OEM

Support, Innovation) and Advance Systems

170-200

The AI research centre targets "Human-Centric AI“ for

areas such as emotion recognition and medical

diagnostics. Other Focus Areas include WiFi Firmware,

Radio Firmware and developing connectivity IP for SoC

chips.

800-900Primary focus is on designing scalable, energy efficient-

processors and physical intellectual property (IP) for

sensors, servers, smart phones, tablets, enterprise

infrastructure and the Internet of Things.

80-100Toshiba CRL focuses on Quantum Information, Quantum

Key Distribution and Semiconductor quantum dots, Speech

Technology, automatic speech recognition and Computer

Vision.

SPINEX : AI Platform for B2B applications

50-60

Key focus is on software and hardware development for next

generation mobile multimedia products including

innovations in high-performance graphics, video, audio and

gaming on portable devices, mobile TV, DSL modems and

next-generation broadband technologies.

80-100

100-150

450-500

30 - 40

20-30

30% 5%

5%

40%

0%0%

10%

10%

5%

0% 0%

6% 4%

0%

5%

70%

60%

0%

40%

30%

40%

75%

0% 4%

2% 0% 10% 10%

0% 0%

4%

5%

30%0%

10%

0% 0-25% 25%-50% >50% Engineering Talent Digital Talent

Note : DRAUP’s proprietary talent module was used to analyse jobs by top companies and skill type26

27

Semiconductor Industry - Talent Maturity Analysis: Over 65% of the employed digital talent in Security and IOT Job families have 10+ years of experience

29% 32% 33%

15%

33%

14%

29% 21%

33%

20%

33%

16%

42%47%

33%

65%

33%

70%

Data Science Software Engineer Cloud Security UI/UX IoT


~150 ~600 ~50 ~150 <50 ~900


Semiconductors Talent~1,900Employed Talent is





28

Semiconductor Industry - Technology Focus: Embedded System Software and Autonomous Driving are the major focus areas across IOT

Other emerging research areas include development of AI-based touch sensors (Cambridge Touch Technologies), IoT SoC Systems (ARM), Image Enhancement and Object Tracking Processors (ARM)

Qualcomm and ARM are also developing IoT platforms as well as software development kits for applications in Autonomous Mobility, Connected Devices and Telecommunication devices such as Modems

Major semiconductor companies like ARM and Qualcomm are focusing on developing end-to-end capabilities. With focus on developing data management, device management and connectivity management services

INSIGHTS

ARM is leveraging Artificial Intelligence & Machine Learning technologies for developing ML-based processors to increase the performance and efficiency of smartphones, autonomous vehicles and data centers

Hiring Matrix



Talent Maturity


HighLow

High

Em

plo

ye

d T

ale

nt

Po

ol

Ind

ex

Hiring Matrix

Automatic

Speech

Recognition

Chatbots

Voice

Recognition

Autonomous

Driving

Sensors

Embedded

Systems

Softwares

Embedded

OS

Embedded

Testing

Softwares

IoT SoC

Systems

Connected

Vehicles

Image

Enhancement

Object

Identification

& Tracking



3D Modelling

Connected

Devices

ML-based

Processors

S/W Dev.

Security

AI/ML

Cloud

Computer

Vision

IoT

UI/UX

Design

NLP

Note: Analysis is based on the DRAUP’s proprietary engineering database28

29

Life Sciences : Cambridge is the third largest Biotech cluster in the world, attracting top tier companies to set up research centres and leverage the Bio-tech ecosystem

51Nobel Prize winners in Chemistry and Medicine

affiliated to University of Cambridge

~61%Of start-ups with funding >$ 10m are in

Biotech / life sciences

~180Biotech R&D, and Pharmaceutical

manufacturing firms in Cambridge

2.95Total Science Patents per 10,000 working age

population, only behind Boston and San Diego

Major Science Parks in CambridgeBiotech/Pharma Start-ups have raised $16.4 B, more than 3 times the next biggest category, enterprise software

Cambridge Science Park

~40 St John’s Innovation Centre

~10

Cambridge Biomedical Campus

~20

Babraham Research Campus

~40

Top Company Activity

Abcam moved to a bigger facility in Cambridge Biomedical campus with plans to increase focus on new age tech areas

China based Novogeneestablished it’s first European genomic sequencing centre at Babraham Research Centre Molecular

Immunology

Therapeutics for rare diseases

Therapeutics in Oncology

Therapeutics in Oncology

Epigenetic Tools

Key Start-ups Area

~xx : No of biotech/ life science

companies in the Science Park

$448 M

AstraZeneca, MedImmune, One Nucleus, and RxCelerate launched a bio-incubator and life sciences accelarator at BabrahamResearch Campus

Note: 210 Start-ups founded after 2010 were analysed for this study


30

Life Sciences : AstraZeneca and Illumina have high AI/ML talent pool while other MNCs have high Software development talent

1500-160070% 10% 0% 10%

Main focus is on using AI for drug discovery, synthesis of

molecules and imaging, Recurrent neural networks &

Reinforcement learning, Cognitive computing, IoT, AR,

VR and mixed reality technologies for Cardiovascular,

Oncology & Neuroscience applications

Human Longevity Inc.: 10 year deal – gene sequencing

200-25070% 20% 0%

Main focus is on AI based digital diagnostic solutions,

development of digital pathology using AI, networked digital

pathology, home healthcare solutions and disease

management

50 - 6025% 0% 50% 0%

5%

15%

Products/TechnologiesAI/MLComputer

Vision

Software

DeveloperSecurity UI/UX IoT

80 - 100

60 - 80

20 - 25

NLP

15%

Majority of engineering focus is on algorithm design,

application of deep/ML for health data analysis, gene

sequencing & diagnostic applications.

100,000 Genomes Project: Gene sequencing for cancer

patients and rare diseases

40 - 500% 0%

5 - 10

Main focus is on Drug development, global patient safety,

oncology, Haematology/ Oncology Bone & Neuroscience,

Bone and Metabolic Medicine

100 - 15095% 0%

Majority of focus is on cell and gene therapy discovery,

adoptive T-cell therapeutics, Specialist oral health and

translational medicine0%

20 - 30

0% 0%

0% 0%

5% 15%

5% 5%

0% 0%

0%

0%

0%0%

50% 50%

0% 0-25% 25%-50% >50% Engineering Talent Digital Talent

Note : DRAUP’s proprietary talent module was used to analyse jobs by top companies and skill type 30

31

Life Sciences : Talent Maturity Analysis - Over 50% of the employed digital talent in Security, Data Science and IOT Job families have 10+ years of experience


HealthCare Talent~950Employed Talent is


29% 32% 33%

15%

33%

6%

33% 33%

21%21%

33%

20%

33%

16%

33% 33%

50% 47%

33%

65%

33%

74%

33% 33%

Data Science Software Engineer Cloud Security UI/UX IoT Computer Vision NLP


~250 ~350 <50 ~100 ~50 ~150 ~100 <50




32

Life Sciences: Technology Focus- Health Data Analytics, Gene Sequencing and Chronic Rare Diseases Management are the emerging capabilities in health care with high AI/ML innovation

INSIGHTS

Hiring Matrix



Talent Maturity


HighLow

High

Em

plo

ye

d T

ale

nt

Po

ol

Ind

ex

Hiring Matrix



Genomics

Data

Analytics

Therapeutics

Gene

Sequencing

Medical

Robotics Medical

Imaging

Chatbots &

Voice

Interfaces

Remote

Health

Monitoring

Health Data

Analytics

Digital

Diagnostics

Connected

Medical

Devices

Virtual Drug

Development

3D Modelling

Chronic &

Rare Disease

Management

Prosthetics

Molecule

Design

Software

Drug

Discovery

S/W Dev.

Security

AI/ML

Cloud

Computer

Vision

IoT

UI/UX

Design

NLP

Astrazeneca is developing connected devices such as connected inhaler for Asthma patients and health monitoring systems.

Companies such as Astrazeneca and Cambridge Cognition are working on applications of AI/ML for Drug Discovery & Development, Digital Diagnostics and Therapeutics development

Illumina is leveraging AI/ML technologies for Gene Sequencing and Genomic Data Analysis

GSK used Luminoso’s NLP and text analytics technology to create a database and study patterns in patients’ concerns about vaccination so as to incentivize childhood vaccination.

Note: Analysis is based on the DRAUP’s proprietary engineering database32

Start-ups Analysis

33

Start-up Ecosystem : Cambridge is home to 210 funded Start-ups with an accumulative funding of $1Bn

Source: DRAUP Startups Module – Includes startups across major geographies such as US, Canada, Israel, Europe, China and India. Coverage may be limited in China and other south east APAC

regions. The list above is updated as of May, 2017

~60% of VC funds have been raised in last 3 years

30% YoY growth in number of start-ups since 2010

Highest Exits in Biotech & Enterprise Software

2010 2011 2012 2013 2014 2015 2016 2017 2018

$60 $73 $88

$137

$216

$432

$698

210129 159997347 19618427

YTD*

~$1Billion USD

Cumulative Funding

~$0.04Billion USD

No. of Start-upsx

34

35

Start-up Ecosystem : Life sciences/Biotech start-ups received ~47% of the total funding, major focus areas include - AI Imaging, Clinical NLP and Robotic Surgery

~$1 B

~210

• MA- Media & Advertising

• FT- FinTech

Okiki app enables movie viewers to connect with each other/celebrities via chat and live-streaming.

Fo

cu

s

Inte

nsit

y

LOW

HIGH

Clinical NLP

14%4%5%8%34%35%

Start-ups across sub-verticals

Home Automation

Augmented/Virtual

Reality

Autonomous Drone

Delivery

AI Image Classification

Robotic Surgery

UI/UX

Advertising Analytics

ML based Content

Delivery

AI/ML

Analytics

Digital Banking

Fraud/ Risk Analytics

Blockchain Technology

Software Development

Disruptors

DarkTrace uses AI and unsupervised ML to autonomously detect and fight cyber attacks across all digital environments

Use Cases

Kymab leverages AI Image classification for Antibody discovery, vaccines, & Innovative Antibodies

SyndicateRoom’s unique Algorithm draws on data from the investment decisions of lakhs of sophisticated investors to determine which companies to invest in.

5%4%4%2%47%38%

Software/ Internet Healthcare MA Telecom FT Others

Funding

Start-up Count

Focal Point Positioning developed a next generation navigation & positioning software for smartphones, wearables & autonomous vehicles leveraging IoT

Focal Point

Positioning

Note: Data curated by DRAUP Start-up module and updated in Nov 2018

Note: The list above is non-exhaustive

35

Source: DRAUP Startups Module – Includes startups across major geographies such as US, Canada, Israel, Europe, China and India. Coverage may be limited in China and

other south east APAC regions. The list above is updated as of May, 2017

Cloud

AI/ML

Computer

Vision

IoT

Software

Technology Talent Pool Unicorns Roles and Skills Scale

~100

• Data Scientist

• ML Engineer

• Applied Scientist

• Cloud Engineer

• Cloud Enterprise Architect

• Cloud Infrastructure Engineer

• Cloud Architecture Engineer

UI/UX

~200

~100

~1300

~3000

~2500

• Embedded Software Engineer

• Principal System Engineer

• Senior DSP Engineer

• Software Lead Engineer

• Software Engineer

• Full Stack Developer

• Senior Software Developer

• Web Developer

• Frontend Engineer

• UI Designer

• UX Developer

• Interaction Engineer

• Computer Vision Engineer

• Computer Vision Research Engineer

• Senior Computer Vision Engineer

• Computer Vision Technologist

~16%

~4%

~6%

~10%

~5%

~5%~4%

~13%

~10%~8%

~5%

~5%

~2%~1%

~3%

~5%

~1%~2%

~1%

~1%

~2%~1%

~1%

Lateral Hiring Targets: MNCs can target a host of scaled start-ups to leverage their mature talent pool

36

Top Patent-filing Start-ups

Industry Patent Use Case

Semiconductors• Flexible fingerprint sensors• Flexible OLED displays• Glass-free organic LCD

Life Sciences & Biotech

• Portable surgical robotic systems for minimal access surgery (endoscopy & laparoscopy)

Enterprise Software- AI/ML

• Network security using AI in both IT & OT environments

• Anomaly alert system for cyber threat detection using in-house ML techniques

Enterprise Software- Security

• Data protection in Trustonic products’ (TEE or TAP) technology implementations

• Security system for Kinibi based devices providing REE state monitoring

Enterprise Software- Security

• Device security using genome data

Enterprise Software- IoT

• Communicating between applications, running on different nodes, having logic in differing languages to monitor and control multiple devices with one unified interface

Industry-wise Patents filed by Cambridge Start-ups

~90% of Total

patents files

4

5

0

1

6

44

3

3

9

21

73

53

Energy &Environment

Aviation &Aerospace

Chemicals

Enterprise Software

LifeSciences &Biotech

Semiconductors

Granted Pending

Patents filed by

Cambridge Start-ups in UK222Between 2010 & 2018

Patents: Semiconductors, Life sciences/Biotech and Software/Internet Startups filed ~90% of all start-up patents

Note: The represented data has been derived using DRAUP Proprietary Talent Database37

38

Start-up case study: Darktrace and GeoSpock

Source : ZinnovSource : ZinnovSource : Zinnov

Leadership

Darktrace Antigena autonomously interrupted

a ransomware attack at a telecommunications

firm. It detected a suspicious SMB encryption

activity within 9s and stopped the attack by

revising its understanding of deviation

Uses AI and unsupervised ML to autonomously detect and fight cyber attacks across all digital environmentsEnterprise Immune System: Passively analyses raw network traffic to independently learn to

detect significant deviations and alert the organization to emerging threats.

Darktrace Industrial: Detects cyber threats by monitoring network traffic across both OT and IT to

conceive a normal pattern for the user/system and identifying potential threat at an early stage

Products

Funding $229.5 M

Investors

Employees ~750

DAVE PALMERDIRECTOR OF TECHNOLOGY

POPPY GUSTAFSSONCO-CEO

NICOLE EAGANCEO

Funding $17.5 M Employees ~50

Case Study

Top Job Roles Work Load

• Leverage machine learning and artificial intelligence for the detection of and response to network anomalies

Cyber Security (MachineLearning ) Analyst

Leadership

Geospock suite can help in harnessing data of time and location used in designing strategies for smart cities like trend/correlation analysis, prediction models, evidence-based decisions, etc

Help in handling extreme-scale data in real-time using big data engineering infini8: Used for data indexing to preserve large scale data in its propriety data storage solution

extrapol8: Enables both general and specialist data analytics

Illumin8: Used for data visualization for geospatial analytics

Products

InvestorsCase Study

Top Job Roles Job Load

RICHARD BAKERCEO

STEVE MARSHFOUNDER, CTO

IAN HAMMONDCOO

~ 55

Software Developer ~ 20• Designing and implementing web applications• Conducting code-reviews and end-to-end testing• Architecture design and focusing on clean code/design usage

Cyber Security Engineer ~ 10• Work on-site with the client to develop internal cyber security systems for

them• Build custom solutions and provide troubleshooting services

• Identifying, analyzing and determining the root cause of Advanced Persistent Threats, network anomalies and unusual activity within a client network

CyberDefense Specialist ~ 30

• Develop high-performance visualizations of very large scale geo-temporal data• write scalable and well-engineered code using JavaScript, React, HTML, CSS,

GraphQL and WebGLSoftware Engineer/Developer ~ 15

• Analyze large-scale heterogeneous datasets using data modeling, software development, statistics, data interpretation, machine learning and data visualization

Data Scientist ~ 2

• Analyze data in petabyte-scale to build predict analytics models• Use latest tools and techniques in the ML/AI space combined with GeoSpocks

data processing technology• Co-ordinate with internal platform and infrastructure teams to get algorithms

running at extreme scale

Machine Learning Engineer ~ 2

Note: The represented data has been derived using DRAUP Proprietary Start-up Database 38

39

Start-up case study: Kymab and Mission Therapeutics

Source : Zinnov

Leadership

Granted Novo Nordisk licence toKymouse™ with access to transgenichuman antibody mouse strains, togenerate highly selective, potent,human antibody drugs

Therapeutic Antibody: Captures diversity of the B lymphocyte component of immune system and generates antibody-based biopharmaceuticalsVaccines: Immunogen discovered through Kymouse™ elicits a protective immune response to a given pathogen to treat the disease

Products

Funding $230M

Source : Zinnov39

Investors

Employees ~ 200

David ChiswellCEO

Allan BradleyFounder

Arndt SchotteliusExec. VP

Funding $128M Employees ~50

Case Study


Support pharmacology scientists with in vivo and ex vivo work. Research Associate

Leadership

Collaboration in the research andpreclinical development of specifiedDUB inhibitors for the treatment ofAlzheimer’s Disease and Parkinson’sDisease

Chemistry Platforms: A customizable platform with novel chemistries for DUB-targeted therapeutics to enhance target selectivity and drug potencyPatents: Mission is protecting its platform and pipeline with many patent filings covering target validation, proprietary assay development

Products

InvestorsCase Study


Dr. Anker Lundemose CEO

Prof. Steve JacksonFounder

Dr. Paul WallaceCBO

~ 60

Research Scientist ~ 40

Biomarker Developer ~ 10

Formulation and characterization of nanoparticles Drug with experience in Immuno-oncology

Contribute scientifically to inception and realization of biomarker discovery and development

Bioinformatician ~ 5Application of data analysis and machine learning methods to biological and medical product development.

Develop & support projects in biochemistry/molecular biology, such as assay development & protein production

Research Scientist ~ 20

Drug development from target validation to pre-clinical with expertise across range of in-vitro and assay validation.

Principal Scientist

Responsible for all aspects of pharmaceutical IP for in-house patent department

Patent Attorney

Discovery and drug development in metabolic disease with focus on diabetes, cardiovascular disease and obesity.

R&D Project Manager

~ 10

~ 5

~ 5

Note: The represented data has been derived using DRAUP Proprietary Start-up Database39

40

Start-up acquisition analysis: Acquisitions – Majority of acquisitions are happening in AI/ML and Security segments

Technology and market expansion are primary drivers for M&A

0% 5% 10% 15% 20% 25% 30%

Big-Data Analytics & BI

ArtificialIntelligence/ML/Computer

Vision/NLP

Embedded Systems/IoT

Software & UI/UX Development

Security

Cloud Technology

Virtual Reality & 3D

Acquisitions of ~100 start-ups by Technology Type

Start-up count by %

Apple acq. VocalIQ

$70M

Acquisition Driver

Apple acquired Vocal IQ , a University of Cambridge spin-out. Objective of theacquisition was to enhance the capability of speech recognition technologyfor Siri , as Vocal IQ had created the world's first self-learning dialogue API.

Bolster Technology Stack

Amazon acquired Evi Ltd, a technology based company focused on knowledge systems and semantic search engine. This addition propels Amazon’s current offering of its voice-driven AI assistant Alexa.

Enter New Markets

Amazon acq. Evi Ltd

British Gas acq. AlertMe

British Gas acquired AlertMe, a Home-based IoT devices company. The purchase will help British Gas with an opportunity to be the leader in intelligent connected home services.

Acquihire Talent

$100M

Huawei Tech. acq. Neul

Huawei acquired Neul Ltd, a IoT based connectivity firm with the aim to bring new Internet of Everything applicative products into its portfolio for EU region

Build New Products$25M

$26M

Source: DRAUP Proprietary: SWARM Disruption Framework for Start-up Analysis40

University Analysis

41

42

University Ecosystem : 6 universities supply a fresh talent of ~9000 IT/Computer engineering talent annually; majority of software talent graduated, contribute to Life science industry

• Oxford, Cambridge and London

(Golden triangle) houses the UK’s

largest biomedical cluster with

around 170 Medical biotechnical

companies linked to universities

• Universities of the Golden Triangle

work collaboratively with initiatives

like G5, Global Medical Cluster,

MedCity, and SES, to ensure that

the Golden Triangle becomes a

global science and innovation hub

• Latest 'AI and Big data' courses at

competitive enrolment fee attracts

UG and PG talent from across the

globe, paving the way for

fundamental research into data

analysis and machine learning with

applications in Computer science,

Medicine and Technology

Universities/ colleges Landscape in Golden triangle

Most common courses pursued

• Biotechnology

• Computer Science

• Information technology and Telecommunications

35%

27%

24%

9%

5%

Life Science Humanities Computer &Engineering

History &Arts Economics

Course Adoption trend

Major Universities in and around Cambridge 6

Software/Computer graduates from the 6

universities~9k

Software/Computer graduates from

universities in Cambridge ~900

Total Graduates ~60k

Contribute to software talent

Note : DRAUP’s Talent Module analysed universities in Cambridge and nearby locations to identify top universities and key courses

Top Universities/ colleges in Golden triangle

42

43

University Ecosystem : Maturity of courses offered by top universities/colleges

Top AI/ Big Data Talent Universities Beginner Courses Intermediate CoursesAdvanced

Courses

UNIVERSITY OF CAMBRIDGEJava & Object-Oriented Programming, Operating

Systems, Discrete Mathematics & Algorithms,Human-Machine Interaction

Machine Learning and Real-world Data, Artificial Intelligence, Concurrent and Distributed Systems,

Software and Security Engineering,

Mobile Robot Systems, ML and Bayesian Inference, Multicore Semantics and Programming, NLP,

Computer Vision, Cloud Computing, Data SciencePractices

ANGLIA RUSKIN UNIVERSITYComputer Gaming Technology, Cyber Security,

Artificial Intelligence (Basic), Basic Maths for Technology, Computing and Information Systems

Core Mathematics for Computing, Network Routing and Switching Essentials, Digital Security, Digital Data

Storage and Transmission

Network simulation and modelling, Internet Services, Data Analytics and the Cloud, Image Processing, Data

Structures and Algorithms

UNIVERSITY OF OXFORDFunctional & Imperative Programming, Linear

Algebra, Probability, Design and analysis of algorithms, Discrete mathematics

Concurrent programming, Intelligent systems, Machine learning, Geometric modelling, Lambda

calculus and types

Probabilistic model checking, Probability and computing, Advanced Security, Quantum Computer

Science, Natural Language Processing

KING’S COLLEGE, LONDONProgramming Practice & Applications, Computational & Mathematical Thinking, Statistics for Data Analysis,

Computer Systems

Practical Experiences of Programming, Introduction to Artificial Intelligence, Internet Systems, Data

Structures, Data Mining

Artificial Intelligence Reasoning & Decision Making, Cryptography, Natural Language Processing, Artificial

Intelligence Planning

IMPERIAL COLLEGE LONDONComputer Architecture, Computational Optimisation, Mathematics for Machine Learning, IoT, Information

and Coding theory

Visual Computing and Robotics, Computer Vision, Statistical Machine Learning and Pattern Recognition

Dynamical Systems and Deep Learning, Advanced Security, Computer Vision, Advanced databases,

Quantum Computing

UNIVERSITY COLLEGE LONDONTheory of Computation, Principles of Programming,

Logic and Database Theory, Digital Security

Networking and ConcurrencySecurity, Database and Information Management

Systems, Data-Mining

Artificial Intelligence and Neural Computing, Crypto Analysis, Computer Vision, NLP

Courses offered by Top Universities/Colleges

Note : DRAUP’s proprietary talent module was used to analyse millennial moments across various cities

Cambridge based universities Universities outside Cambridge

43

44

Total Enrolment:

~20,000

Total Undergraduates:

~12,000Computer Science:

~300

Total Post Graduates:

~7,200Computer Science:

~315

45+ Courses

Tech Collaboration & COEs University CollaborationKey Startups Born Venture funds /Accelerators

Collaboration

University of Cambridge : Leading tech giants such as Google, Microsoft, and Huawei have collaborated with University of Cambridge for research in the field of AI, and Deep Learning

Note : DRAUP’s Talent Module analysed 100,000+ global universities to identify top universities and key courses in software engineering, ML and Big Data

VENTURES• 250+ firms founded by Computer Lab

Alumni• ~200 Ventures at Accelerate

Cambridge• >60% of ventures are based on AI/ML

new Technologies.• ~100 Ventures Working in

Lifesciences/biotech

ACCELERATE CAMBRIDGE PROGRAMTo enable and Nurture venture creation out of the university of Cambridge

Microsoft Research has

collaborated with University

of Cambridge in Machine

Learning to provide support

for Ph.D. students & also

offers positions at Microsoft Research Lab

University of Cambridge, BT

and Huawei have announced

a new five-year initiative to

establish a joint research and

collaboration group at the

University of Cambridge.

CU launched a DeepMind

Chair of Machine Learning

to build on a wide range of

AI related research.

ImprobableRaised $ 502 M from

SoftBank

PROWLER.ioRaised $ 13 M from

Cambridge Innovation Capital

VocaliqAcquired by Apple

University of Cambridge collaborated

with MIT for projects such as Aesthetic

Imaging, Emotionally Intelligent

Surfaces etc

University of Cambridge collaborated with

USC for projects related to Computational

Aesthetics, Computing & Intelligent

Interaction etc

University of Cambridge collaborated

with IIT Bombay for ongoing research on

Nanotechnology with focus on enhancing

micro-scale precision sensing

technology.

$9 Mn

$1.9 Mn $5.5 Mn

44

University Collaborations: Tech giants have majorly collaborated with University of Cambridge for co-innovation, skill enhancement and setting up of digital labs/research centres

Note : The above analysis is based on the DRAUP’s proprietary engineering database and insights from industry stakeholders, updated as on Aug, 2017

Microsoft and University of Cambridge took a strategic step to

modernize engineering curriculum by providing Azure

notebooks to the Students

Microsoft AI Residency program is a collaborative coursework

with University of Cambridge which bolsters application of AI in

the fields of Healthcare, Biotech and Education

Skill Enhancement

Digital Lab/Centre Co - Innovation

Investment/Deal

Low High

Corporate Collaborations

Nokia and University of Cambridge partnered on joint research

projects on Nanotechnology at Nanoscience Centre and

Electrical Engineering Division

Research agreement is signed between University of Cambridge

and AstraZeneca to lower the engagement and regulatory

barriers and speed up the research

The University of Cambridge, BT and Huawei signed a new five-

year initiative which focus photonics, digital and access network

infrastructure and media technologies

HP signed $210 million agreement with Cambridge University

Hospitals to create a secure, robust, integrated IT environment

that allows clinical staff to access a unified view of each patient’s

clinical and administrative information via its new electronic

patient record system.

Nokia Bell Labs is a founding partner of the new Centre for

Mobile, Wearable Systems and AI, to be based in University of

Cambridge

AstraZeneca is currently working with Microsoft and the

University of Cambridge at IMED Biotech Unit to work in cancer

research more effectively

GSK has its only trials unit in UK in the Cambridge Clinical Trials

Unit which has the long-term ambition of jointly delivering new

medicines to patients in the next five to ten years

Established the Omeros Center at Cambridge for Complement

and Inflammation Research for wide range of diseases including

thrombotic microangiopathies, kidney diseases and central

nervous system disorders

Boost drug formulation. It helps patients to more easily absorb

poorly soluble drugs administered orally via tablets and capsules

Intensity showing number of corporate collaborations

45

46

46

University of Cambridge : University of Cambridge has 60+ professors/lecturers focusing on new age digital technologies

Department of Computing and Technology Research (60+ Faculty members)

Artificial

Intelligence

Group

5 Faculty Members

2 Researchers

18 Students

Research Focus Genomics and

Bio- Informatics,

Computational

Theory,

Computer Vision,

Cognitive Science

Computer

Architecture

Group

7 Faculty Members

10 Researchers

12 Students

Research Focus Languages and

compilers for

multi-core

architectures,

Processor

Architecture,

Programmable

processing

substrates,

Resilient cloud

computing

Digital

Technology

Group

14 Faculty Members

13 Researchers

18 Students

Research FocusLow-Power

Microprocessor

Design,

Channel Coding

and Signal

Processing for

Wireless

communications,

Wireless Sensor

Networks,

Cross-Layer

Wireless Access

Graphics and

Interaction Group

5 Faculty Members

8 Researchers

9 Students

Research FocusGraphics and

imaging,

Interaction and

design,

Affective

computing,

Stereoscopic

displays,

Aesthetic imaging,

Personal projected

displays,

Inclusive user

interfaces

NLP Group

6 Faculty Members

8 Researchers

24 Students

Research FocusSpatial & Personal

Adaptive

Communication

Environment,

Feedback for User

Adaptive Statistical

Translation,

Computational

Natural Language

Processing and the

Neuro-Cognition of

Language

Programming

logics &

Semantics

14 Faculty Members

6 Researchers

14 Students

Research FocusProgramming

language design,

Development of

interactive theorem

provers,

Development of

automatic proof

procedures, Formal

verification of

computational

systems, semantic

models using

techniques such as

structural

operational

semantics

Security Group

7 Faculty Members

11 Researchers

11 Students

Research FocusBanking security,

Biometric

identification,

Microcontroller

security ,

Robustness of

cryptographic

protocols,

Quantum

Cryptography,

Security of Clinical

Information

Systems,

Information hiding

Systems

Research Group

10 Faculty Members

9 Researchers

22 Students

Research Focus On Content

Indexing for Off-

Path Caching in

Information-Centric

Networks ,

Scalable Provision

of Semantically

Relevant Web

Content on Big

Data Framework ,

Hybrid Renewable

Energy Routing for

ISP Networks,

Blockchain-enabled

Wireless Mesh

Networks

Reference:1. Faculty Members – Professor / Lecturer2. Researcher – Post Doctorate Researcher3. Student – PhD Students

Systems

Research Group

Note : The above information is based on data provided by University of Cambridge and DRAUP Proprietary Database

47

University of Cambridge - Professor Profile

Research Works

Student Profile

Post doc PhD Others

Jose Miguel Hernandez LobatoUniversity Lecturer in Machine

Learning, Department of

Engineering


Email: jmh233-at-cam.ac.uk

Phone: +44 (0) 1223 738 513

Design and implementation of scalable methods

for approximate inference and construction,

evaluation and refinement of probabilistic models

that describe the statistical patterns present in the

data

Research Highlights

Research Goal:Design of model based machine learning which focuses on

probabilistic learning techniques on Bayesian optimization, matrix

factorization methods, copulas, Gaussian processes and sparse

linear models

Reported Topics: A General Framework for Constrained Bayesian Optimization using

Information-based search

Expectation Propagation in Linear Regression Models with Spike and slab

Priors for Machine Learning

Development at Lab

Model-based machine learning: designing

machine learning algorithms that are

specifically tailored to each new application

Bayesian framework: Variables in the

probabilistic model areencoded using

probability distributions. Bayes’ theorem is then

used to combine these probability distributions

with the observed data

Uncertainty Decomposotion in Bayesian

Learning with Deep Generative Models

Publications

~10

Ongoing research initiatives: Implementation of scalable methods for

approximate inference, construction, evaluation

and refinement of probabilistic models

Statistical patterns for data in Bayesian Machine

Learning

B.Sc. in Computer Science, Autonomous University of Madrid

M.Sc. in Computer Science, Autonomous University of Madrid

Ph.D. in Autonomous University of Madrid

Education

Student Research Support

Ross Clarke

PhD Student, University of Cambridge

• Suárez A: Linear Regression Models with Spike-and-slab Priors

• Depeweg S: . Decomposition of Uncertainty in Bayesian Deep Learning

for Efficient and Risk-sensitive Learning

Research Supported / Co-Authored:

NA 5 6

Source : The above information is based on data provided by University of Cambridge

Note : DRAUP has analyzed top professor profiles based on their number of publications and ongoing research initiatives

47

48

University of Cambridge - Professor Profile :

Research Works

Student Profile

Post doc PhD Others

Alastair Beresford

Senior Lecturer

Department of Computer Science


Email: arb33 at cam.ac.uk

Phone: +44 1223 763597

Designing and building novel prototype

technologies, by measuring the human behaviour

that focuses on networked mobile devices, such

as smartphones, tablets and laptops

Research Highlights

Research Goal:Examine the security and privacy of large-scale distributed computer

systems and networked mobile devices, such as smartphones, tablets

and laptops.

Examine the security of devices for the security and privacy problems

induced by the interaction between mobile devices and cloud-based

Internet services

Reported Topics: TIME-EACM project - Explored how sensor networks and distributed systems

can be used to improve traffic and transport

Cambridge Mobile Urban Sensing Project - measured and monitored air

quality, particularly urban pollution generated by motor vehicles

Development at Lab

Nigori: storing secrets in the cloud: build

a secure mechanism for storing sensitive user

data on servers connected to the Internet

tailored to each new application

STRIDE: improve the delivery of real-time and

historic transport and traffic data

Publications

Ongoing research initiatives: TRVE Data

Cambridge Cybercrime Center

Device Analyzer

Isaac Physics Platform

Wearable Systems and Augmented Intelligence

B.Sc. in Computer Science, University of Cambridge

Ph.D. in Department of Engineering, University of Cambridge

Education


Stan Zhang

PhD Student, University of Cambridge

• Martin Kleppmann: Secure Messaging to Secure Collaboration

• Victor B.F. Gomes: Verifying strong eventual consistency in distributed

systems


NA 4 6Journals Others

1252



48

49


Research Works

Student Profile

Post doc PhD Others

Dr Sean B Holden

Senior Lecturer



Email:sbh11 at cl.cam.ac.uk.xx

Phone: : +44 (0)1223 763725

Analysis of error estimation techniques within a

framework based on Probably Approximately

Correct (PAC) learning

Research Highlights

Research Goal:Design and underline the links between bounds and combine the

improvements into a single bound. Combine the PAC-Bayes

approach for randomized predictions with the optimal union bound

using generic chaining technique for variance of the combined

functions

Reported Topics: Support Vector Machines for QSAR - designed a single compound to search

chemical space for elimination of compounds with desirable properties such

as toxicity or "drug-likeness"

Quantum computation applied to machine learning - performed computations

considered intractable (in the formal sense) for any standard (non-quantum)

computer

Software Development at Lab

HasGP - Gaussian Processes in Haskell-Implementation of Gaussian process for

regression and classification based on the

treatment

Bayesian Hierarchical Ordinal

Regression – Matlab code for the material in

paper: "Bayesian Hierarchical Ordinal

Regression”, proceedings of the International

Conference on Artificial Neural Networks

The Generalized FITC Approximation -Matlab code for material in the paper: "The

Generalized FITC Approximation”, proceedings

of Neural Information Processing Systems

Publications

~32

Ongoing research initiatives: Theoretical models for supervised learning –

aims to prove bounds on the performance of

learning systems

Bayesian inference

B.Sc. in Electronic Systems Engineering, University of East

Anglia

M.Sc. in Intelligent Systems, University College London

Ph.D. in Cambridge University

Education


Nicholas Pilkington

PhD Candidate, University of Cambridge

• Richard Russell: Planning with preferences using maximum satisfiability

• Andrew Naish-Guzmann: Thesis Sparse and Robust Kernel Methods

• Ulrich Paquet: Bayesian Inference for Latent Variable Models


1 NA NA



49

50


Research Works

Student Profile

Post doc PhD Others

Hatice GunesSenior Lecturer



Email:

Hatice.Gunes(@)cl.cam.ac.uk

Phone: NA

The Bimodal Face and Body Gesture Database

(FABO) for Automatic Analysis of Human

Nonverbal Affective Behavior to combine face

and body, enabling significant future progresses

in affective computing research

Research Highlights

Research Goal:Focus on Digital Personhood through the ‘EPSRC Being There’

Project that aims to produce greater social integration of robots in

public spaces, and to increase access to public spaces in robot proxy

forms.

Reported Topics: Applied machine learning

Computer vision

Human-robot interaction

Social signal processing

Social robotics

Artificial Emotional Intelligence


Quantised Local Zernike Moments

(QLZM) - Challenge visual feature extraction

for affect recognition on the AVEC'12 Dataset

Probabilistic Subpixel Temporal

Registration (PSTR) – Probabilistic Subpixel

Temporal Registration for Facial Expression

Analysis

Publications

Ongoing research initiatives: The SEMAINE: aims to build a SAL, a Sensitive

Artificial Listener, a multimodal dialogue system

Building a multi-modal/cue module: extract

features from expressive face and upper-body

gestures using computer vision and image

processing techniques

B.S. in Computing Science, Yildiz Technical University

Ph.D. in Computing Science, University of Technology,

Sydney

PGCAP, Queen Mary, University of London

Education


Wenxuan Mou

PhD Candidate, University of Cambridge

• E. Skordos: Multimodal Human-Human-Robot Interactions (MHHRI)

Dataset for Studying Personality and Engagement

• M. Pantic: Continuous Prediction of Spontaneous Affect from Multiple

Cues and Modalities in Valence-Arousal Space


1 3 NA

11 50+22

Journals BookChapters

Others



50

51

Anglia Ruskin

University

Total Enrolment

~22,500

Total

Undergraduates:

~18,000

Total

Post Graduates:

~4,000

Total Researchers:

100+ post doctoral

researchers in CS

University CollaborationsKey Startups Born

(Primarily Technical)Tech Collaboration & COEs

Anglia Ruskin University offers Cisco Certified courses which give you

valuable information and communication technology skills to enhance

student-skillset. Also develop IT networking skills for students and preparing

them for the CCNA certification.

The university has been a Cisco partner since 1999 and trained over 100

instructors and 1000 students

REACTOR

• EU-funded regional development project.

• Growth of applied games sector in the Cambridge shire/Peterborough

region

Anglia Ruskin University: Leading tech giants such as Google, Microsoft, and Huawei have collaborated with University of Cambridge for research in the field of AI, and Deep Learning

PureChimpStartup to help people

with various Skin

Problems

ACTING NOWSocial theatre Company

Uni CompareSocial comparison site

for universities across

the UK

ARU is tied up with Global Education

Institutes. It has varied partnerships,

collaborative programs based on the type of

courses & regions:

1. London (2) & UK (9) Partnerships like

o London School of Osteopathy

o University Centre Peterborough

2. International (14) Partnerships

o Indian School of Business and

Computing - Bengaluru, India

o Budapest Business School - Budapest,

Hungary

3. Distance Learning (4) Partnerships

o Resource Development International

o CNET training

Exemplary Programs

• KEEPs (Knowledge Exchange and Embed

Partnerships)

• Innovation Accelerator Partnerships

• In Neuroscience and Vascular Simulation

established a diverse and collaborative

environment for conducting research.

Note : The above information is based on data provided by Anglia Ruskin University and DRAUP Proprietary Talent Database 51

52

52

Anglia Ruskin University: The University has 20+ professors/lecturers focusing on new age digital technologies

Department of Computing and Technology Research (20+ Faculty members)

Anglia Ruskin IT Research

Institute

15 Faculty Members

8 Visiting Professors

6 Students

Research Focus

• Mobile enabled point of care

solutions to detect

tuberculosis, capture and

analyze images for diagnostics

• Development of IT solutions

for better connectivity

Cyber Security, Networking and

Big Data Research Group

3 Faculty Members

4 Students

Research Focus

• Cyber-based warning systems,

Autonomous threat detection

and threat intelligence, and

neutralization of network-

based attacks

• Next generation software-

defined infrastructure

• Application of machine

learning, data mining and

software defined networks to

make cyber threat big data

more manageable in areas

such as Smart Cities, IoT &

ICS

Informatics, Computing and

Electronics Research

5 Faculty Members

2 Visiting Professors

14 Students

Research Focus

• IOT and cloud computing

• Digital Electronics – SoC,

Embedded systems, FPGA

design, intelligent control, data

fusion

• Graphics, Imaging and Vision

• Image processing and Data

visualization

• Web Technologies, Intelligent

search and Knowledge

modelling

Sound and Game Engineering

and Research

9 Faculty Members -

4 University Professors

5 Lecturers

Research Focus

• Sound synthesis, sound

design, physical and

mathematical modelling,

analogue and digital

synthesisers, microcontrolled

platforms and Internet of

Things for gaming and sound

engineering, digital and real-

world game-based learning,

assisted navigation, virtual

reality and immersive systems,

ultra-portable audio/video

performance system

Reference:1. Faculty Members – Professor / Lecturer2. Student – PhD Students

Note : The above information is based on data provided by Anglia Ruskin University and DRAUP Proprietary Talent Database

53

Anglia Ruskin University - Professor Profile

Research Works

Student Profile

Post doc PhD Others

Dr Alin Tisan

Senior Lecturer


Anglia Ruskin University

Email:[email protected]

Phone: NA

Design of modern sensors and communication

technology, with the advanced electronic devices

such as Field-Programmable Gate Array (FPGA),

algorithms and computer models and Artificial

Intelligence

Research Highlights

Research Goal:Designing AI algorithms in hardware (FPGA) using a developed

integrated hardware-software environment that combines complex

sensors, advanced Electronic Design Automation (EDA) tools and

hardware platforms

Reported Topics: ANN design and FPGA implementation using Matlab/ISE environment

Designing a new infrared temperature sensor

Development at Lab

Managing (processing) acquired data on

hardware and software platforms capable of

hosting different data reduction and artificial

intelligence algorithms

Neuromorphic hardware and system-on-

chip (FPGA) design

Electronic Design Automation (EDA) tools and

hardware platforms

Publications

7

Ongoing research initiatives: Artificial intelligence hardware (FPGA)

implementable

Telemedicine

Smart sensors

Holistic modelling of combined renewable

energy sources

B.S. in Engineering Physics, Babes-Bolyai University

M.S. in Physics, Babes-Bolyai University

PhD in Electronic Engineering, Technical University of Cluj

Education


John Darvill

Ph.D. in Computing, Anglia Ruskin University

• Chin, J: End User platform for implementing Artificial Neutron Networks on

FPGA

• Cirstea, M: SOM neural network design – A new Simulink library based

approach targeting FPGA implementation


NA 2 1

Source : The above information is based on data provided by Anglia Ruskin University


53

54


Research Works

Student Profile

Post doc PhD Others

Jeannette Chin

Senior Lecturer




Phone: NA

Development of end-user programming for digital

home environments to increase the range of

services available from network and networked

devices

Research Highlights

Research Goal:End user programming and machine learning with analytics, and

applications within personalised services, smart or assisted living,

leveraging everyday artefacts and connectivity (IoT)

Reported Topics: Machine learning algorithms

Big data and analytics

End user programming and human machine research

Development at Lab

Publications

Ongoing research initiatives: Machine learning and personalisation

IoT and resilient systems

Big data analytics and semantic ontology

Intelligent environments, digital ecosystems and

assisted living

Human and machine research

B.S. in Internet Computing, University of Essex

PhD in Pervasive Interacting – Human Computer Interactions

Computing, University of Essex

Education


Not Available• V. Callaghan: Understanding and personalising smart city services using

machine learning, The Internet-of-Things and Big Data

• Tisan. A: IoT-based pervasive body hydration tracker (PHT)


NA NA NA

5 296

Journals Book

Chapters

Others

Web Appliance- newly emerging embedded

Internet

iCampus: Pervasive-interactive-

Programming (PiP) paradigm

Machine research, digital ecosystems, signals

processing, analytics



54

55


Research Works

Student Profile

Post doc PhD Others

Alagmir Hossain

Professor



Email:

[email protected]

Phone: NA

Developing a mobile enabled Point-of-Care

(POC) platform to detect TB and to improve

efforts in controlling TB through wider, faster and

low cost 24/7 real-time access

Research Highlights

Research Goal:Use phone’s camera to capture the sample, rather than manually

using colour charts, to eliminate human error and avoid any

subjectivity around interpretation for Tuberculosis diagnosis

Reported Topics: Intelligent Systems and Expert Systems using Artificial Intelligence

Mobile Enabled Expert Systems for Diagnosis

Cyber Security with a particular focus to Phishing

Big Data with a particular focus to Real-time and Optimal Solutions

Development at Lab

Publications

Ongoing research initiatives: Intelligent human-like behaviours in non-player

characters in games

Cyber threat analysis, prediction and detection

in online social networking

Behaviour-based malware detection using

machine learning techniques

B.S. Computer Science

Ph.D. in Automatic control & Systems Engineering, University

of Sheffield

Education


Anjum Shaikh

PhD Candidate, Anglia Ruskin University

• Bourouis. M: Intelligent Mobile based Decision Support System for Retinal

Disease Diagnosis

• Neoh. S: Intelligent facial emotion recognition using a layered encoding

cascade optimization model


NA 6 NA

265

Journals Others

Artificial Intelligence and decision support

system

Intelligent Mobile-Based Diagnosis System

Artificial Intelligence and Neural Network

Mobile phone app to diagnose TB



55

56


Research Works

Student Profile

Post doc PhD Others

Khin LwinSenior LecturerDepartment of Computer ScienceAnglia Ruskin UniversityEmail:[email protected]: NA

Development of real-time intelligent decision

support and knowledge management schemes

for data-intensive applications particularly in

healthcare, transportation, smart cities and cyber

security

Research Highlights

Research Goal:Focus on operational research and artificial intelligence for

applications of modelling, search and optimization techniques to

tackle constrained combinatorial problems to underpin the

development of intelligent decision support systems across a wide

range of real-world applications in healthcare, transportation, smart

cities and cyber security

Reported Topics: Big Data Analytics

Machine Learning and Data Mining

Innovative IoT’s and Smart Cities Applications

Intelligent Decision Support System

Portfolio Optimization

Multi-objective Optimization

Cyber Security

Development at Lab

Publications

Ongoing research initiatives: Intelligent phishing detection in real-time

transaction

An intelligent mobile-enabled expert system for

tuberculosis disease diagnosis in real time

BSc (Hons) in Computer Science, University of Nottingham

PhD in Computer Science, University of Nottingham

Education


• Qu.R: A hybrid algorithm for constrained portfolio selection problems,

Applied Intelligence

• Sabor.M: New Social Engineering Challenges in Phishing – A Case Study

of Ransomware Attack, Cybersecurity


NA 3 NAJournals Others

Big Data & Cyber Security – Manipulate, use,

store and exploit huge amounts of data using

data mining, classification and clustering

methods

Intelligent modelling and Big Data mapping

for the analysis of connectivity and

regeneration

Marzia Hoque Tania

PhD in Artificial intelligence,


114



56

57

Huntingdonshire Regional College

Peterborough Regional College

City College Peterborough

The College of West Anglia

Community / Further Education Colleges In Cambridge-shire (Doesn’t include Cambridge)

4Number of Community Colleges in

Cambridgeshire (Doesn’t include

Cambridge)

~25-27KNumber Of Student Enrolment

Annually

~500-700Total relevant students pursuing IT/

Computer Engineering talent

Most Common IT Courses Pursued

• Network security

• Computer Networking

• Software Development

• ICT Systems & Principles

• Architecture of computer systems

• Software Engineering

Courses On New Age Technologies

• IT Systems security and Encryption – The College of

West Anglia

• Cyber Security – Peterborough Regional College

• Human-computer Interaction – The college of West

Anglia

“Peterborough,

Huntingdon and

Wisbech are the key

hotspots for Community

Colleges in

Cambridgeshire area

apart from Cambridge.

These colleges offer

certification based

courses on technology

areas such as Cyber

security, IT

Infrastructure,

Networking, Application

Development, etc.”

Cambridgeshire UK: Cambridgeshire has 4 Community colleges with only ~2% of total enrolment in Computer Science related courses

Note : DRAUP’s proprietary talent module was used to analyse courses offered in Cambridgeshire 57

58

58

College Overview

Huntingdonshire Regional

College(College changed to

academy in 2017)

Peterborough Regional

CollegeThe College of West Anglia City College Peterborough

Total Enrolment /

Certifications • Total Certifications - 200 • Total Enrollment – 15,500 • Total Enrollment – 10,000 • Total Enrollment – 400

Relevant Programs and

Courses

• Network security

• ICT Systems & Principles

• Information & Creative

Technology

• Software Development

• Cyber Security

• Architecture of Computer

Systems

• IT Systems security and

Encryption

• Human Computer Interaction

• Computer Networking

• Advanced Computing

• IT and Internet Security

Alumni Profiles

James Pepper

IT Technician, HL Hutchinson

Limited

Current works:

• Working on hardware and software

support systems for Windows

Servers desktops and Android and

administer VPN solution

Jonathan Nicholson

Mechanical Designer, BAE

Systems

Current works:

• Design of routed piping to

maintain heating, ventilation and

air conditioning (HVAC) duct

systems using CAD

Mark Jakes

IT Support, PA Consulting Group

Current works:

• Provide 3rd line support to global

users

• Maintain and upgrade SCCM and

involve in the development and

deployment of windows load sets

Jackie Cairns

Mobilisation Associate Manager,

Accenture

Current works:

• Support on solution realization and

service transition activities and

implement the process of operating

infrastructures

Cambridgeshire UK: Community colleges in Cambridgeshire offer Diploma and Certifications courses mainly focused on IT Infrastructure, Security and Design

Note : The above information is based on data provided by the respective Universities and DRAUP Proprietary Talent Database

59

Professor Profiles – Imperial College and University of Oxford

60

Imperial College London - Professor Profile

Research Works

Student Profile

Post doc PhD Others

Dalal Alrajeh

Assistant Professor


Imperial College London


Phone: : NA

Developing techniques and algorithms that exploit

the semantic properties of system models and

domain knowledge, with humans in the loop, to

yield improved specifications. Application

domains include criticial systems for enhancing

security and tackling (cyber-)crime

Research Highlights

Research Goal:Develop a formal underpinning of the classes of explanation and

repair problems for declarative software specifications (described in

Linear Temporal Logic) that may be resolved through learning and

designing suitable logic-based learning algorithms and tools for

learning correct temporal specifications

Reported Topics: Learning Temporal Specifications of Software

Synthesis for Human-Intensive Systems

Automated Elaboration of Correct Software Requirements

Engineering Forensic-Ready Systems

The Social Ecology of Radicalization: A Foundation for the Design of CVE

Initiatives

Building an Intelligent Crime Linkage System

Development at Lab

Logic-based Learning in Software Engineering,

Technical BriefingBayesian Hierarchical

Ordinal Regression

Computer Graphics Forum

Parameterised Verification for Multi-Agent

Systems

Publications

Ongoing research initiatives: Weakest Environment Assumptions Synthesis

for Generalized Reactivity Specifications

Learning Domain-independent Planning

Heuristics

B.Sc. in Information Technology (First Class), King Saud

University

M.Sc. in Computing (Distinction), Imperial College London

Ph.D. in Distributed Software Engineering, Imperial College

London

Education


Mohammadreza Biglari

PhD Candidate, Imperial College London

• Davide Cavezza: Weakest Environment Assumptions Synthesis for

Generalized Reactivity Specifications

• Pawel Gomoluch:Learning Domain-independent Planning Heuristics

• Kari Davies: Building an Intelligent Crime Linkage System (ESRC)


NA 2 NA

1 315

Journals Book

Chapters

Others

Source : The above information is based on data provided by Imperial College London


60

61

Imperial College London - Professor Profile

Research Works

Student Profile

Post doc PhD Others

Dr. Krysia BrodaSenior Lecturer


Imperial College London

Email:kb“at”imperial.ac.uk

Phone: : +44 (0)20 7594 8426

Research at the interface of machine learning,

artificial intelligence, and its Big Data

applications- from creative and effective

computing to human-computer interaction, from

machine vision to neurotechnology

Research Highlights

Research Goal:Data-level machine learning to support feature extraction from data

(“Big Data”) to extract readable and insightful relational knowledge

which supports human-understandable machine inference and also

focus on applying a wide variety of feature-based machine learning

techniques in key application areas

Reported Topics: Neural-Symbolic Integration -logic programs can be encoded into artificial

neural networks with an input and output layer, together with a single hidden

layer

Labelled Deductive Systems (LDS) - provide a uniform approach for

investigating different logics

Development at Lab

Logic and Artificial Intelligence - model

checking methodologies for the verification of

autonomous agents has found applications in

autonomous vehicles, service-oriented

computing and security

Spike – development of frameworks,

algorithms, and effective and scalable systems

for engineering structured and probabilistic

knowledge

Publications

29

Ongoing research initiatives: Distributed Abductive Reasoning (DARE)

Inductive Logic Programming (ILP)

Probability in Logic Programming

Application of Logic Programming to Ontologies

Ph.D. in Machine Learning and Time Series Models

Education


Artur Garcez

Ph.D. in Computing, Imperial College London

• Dr Oliver Ray: Hybrid Abductive and Inductive learning: HAIL

• Calin-Rares Turliuc: probabilistic abductive logic programming, which has

been applied to computational biology


NA 5 NA



61

62

University of Oxford - Professor Profile

Research Works

Student Profile

Post doc PhD Others

Marta KwiatkowskaProfessor



Email:

[email protected]

Phone: : +44 (0)1865 283509

Develop model to describe how systems move

between states by executing actions represented

as state-transition graphs

Research Highlights

Research Goal:Develop modelling and automated verification techniques for stable,

safe, secure, timely, reliable and resource-efficient operation of

computing systems. Design of Model checking verification technique

to deploy certain properties expressed in temporal logic of a system

model

Reported Topics: Noise and Predictability in Molecular Systems

VERIWARE: From Software Verification to ‘Everyware’ Verification

VERIPACE: Design, Analysis and Synthesis Tools for Cardiac Pacemaker

Software

Autonomous Ubiquitous Sensing

Predictable Software Systems

Development at Lab

Complex Systems - Symmetry breaker in

distributed coordination algorithms for

analysing performance and Quality of Service

properties

Prism - Used in distinct fields such as

distributed and cloud computing, wireless

networks, security, robotics, quantum

computing, game theory, biology and

nanotechnology

Publications

Ongoing research initiatives: Mobile Autonomy Programme Grant: Safety,

Trust and Integrity

AFFECTech: Personal Technologies for

Affective Health

B.Sc. in Computer Science in Jagiellonian University

M.Sc. in Computer Science in Jagiellonian University

Ph.D. in University of Leicester

Education


Luca Laurenti

PhD Candidate, University of Oxford

• Maria Svorenova: Research Officer on Mobile Robotics Programme Grant

and ERC project VERIWARE

• Morteza Lahijianian: Research Officer in association with Mobile Robotics

Programme Grant and ERC project VERIWARE


1 10 NA

~300



62

63

University of Oxford - Professor Profile

Research Works

Student Profile

Post doc PhD Others

Alessandro AbateAssociate Professor



Email:

[email protected]

Phone: : +44 (0) 18656 10767

Formal verification and optimal control of

heterogeneous and complex dynamical models,

built from first principles or learnt from data

Research Highlights

Research Goal:Analysis, verification, and optimal control of heterogeneous and

complex dynamical models -- particularly, stochastic hybrid systems --

and their applications in the life sciences and in cyber-physical

systems (particularly involving energy and power networks)

Reported Topics: OXCAV - Stochastic Hybrid Systems, Probabilistic Model Checking

Synthetic Biology

Autonomous Intelligent Systems

Cyber-Physical Systems (Energy Systems and Networks)

Switched, Hybrid, and Discrete-Event (e.g., MPL) Systems


FAUST2- Tool that generates formal

abstractions of (possibly non-deterministic)

discrete-time Markov processes (dtMP) defined

over uncountable (continuous) state spaces

VeriSiMPL - Toolbox used to generate finite

abstractions of autonomous Max-Plus-Linear

(MPL) systems over R^n

DSSynth - Automated Digital Controller

Synthesis for Physical Plants

Axelerator - Tool for reachability analysis of

Open Guarded Linear Time Invariant systems

through the use of abstract acceleration

Publications

Ongoing research initiatives: Analysis and Design of Hybrid Systems

Hybrid Systems: Computation and Control

Hybrid Systems Biology

Numerical Software Verification

B.S. in Electrical Engineering, University of Padova

M.S. in Computer Science and Electrical Engineering, UC

Berkeley

Ph.D. in Computer Science and Electrical Engineering, UC

Berkeley

Education


Joe Brown

PhD Candidate, University of Oxford

• D. Adzkiya: Computational Techniques for Reachability Analysis of Max-

Plus-Linear Systems

• M. Prandini: Approximate Model Checking of Stochastic Hybrid Systems


NA 11 NA

25 43 623

Theses Book

Chapters

Journals Others



63

Demand Supply GAP

64

65

Employed Talent in Digital Job roles is estimated to be ~18K; High demand across these roles can be fulfilled by repurposing adjacent talent pool

1.a

~900* Software Graduates from the 2 Universities

Estimated Job openings across Enterprises and Startups in Cambridge

Total Digital & IT Talent Installed in Enterprises and Startups

~3.4K

~18K

Employed Digital Talent in Cambridge

Employed IT Talent in Cambridge (Talent which can be

upskilled to take up Digital Job roles)

~13.6 K

~4.4 K

Fresh Graduates from Universities

Digital Job Openings

Employed Talent

IT Talent

Digital Talent

Note: : The represented data has been derived using DRAUP Proprietary Talent Module, as of November 201865

Career Progression Case Study: Frequent Progressions from IT Roles to Cloud Computing and Data Scientist job families

• Adobe Dreamweaver CC (2018) - Level 2

• Amazon Web Services: Architecting on AWS

•Probabilistic Machine Learning•Signal and Pattern Processing

• R object-oriented programming and package development

• Bioinformatics: Python for MRI Applications

• Adobe Dreamweaver CS6• Web Authoring: HTML• Drupal: An Introduction

• Cyber Security- Social Media Profiling

• The Cyber Security Programme

• Image Processing and Visualization with LithoGraphX

• Image Processing & Imaging Coding

• Developing computer architectures and computing strategies

• Probabilistic Machine Learning• Signal and Pattern Processing

CLOUD ENGINEER

SOFTWARE DEVELOPMENT

SECURITY

IOT

MACHINE LEARNING

USER EXPERIENCE

COMPUTER VISION

NLP

Certifications offered in Cambridge

Network Engineer Systems analyst DevOps Engineer

IT Consultant Backend Engineer DevOps engineer

Cloud

Engineer

Server Engineer Database Admin

Data Architect

IT Support

Systems Developer

Technical support

Technical Consultant

Database Manager

IT Administrator

Network Analyst

Technical Architect

Network support

Solution Architect

Business Architect

Enterprise Data

Manager

Infrastructure

Manager

ADJACENT IT JOB ROLES

TOTAL HEADCOUNT FOR IT JOB ROLES IN CAMBRIDGE: ~4,400

CAREER PROGRESSION EXAMPLES

Database Admin Backend Engineer Data Engineer

Application

Maintenance

Business

IntelligenceBusiness Analyst

Data Scientist

Note: The represented data has been derived using DRAUP Proprietary Talent Module66

Open Position Analysis - Calibrating degree requirements: DRAUP Open position analysis for Cambridge shows, 29% of the Open positions in IT job roles do not require Bachelors/Masters/PhDs degree

WHO IS REPLACING THEM?

Cambridge Spark provides

continuous professional

development training for

developers and Data Scientists in

24 weeks

Khan Academy is a platform where

experts create content across

various technologies to students to

learn and develop expertise

Coursera is also a content based

platform which offers certification

based technology courses to

students

~29%

10K Jobs

analysed

No-degree

requirement

Backend Engineer

Business Analyst

CAD Design Engineer

Data Scientist/Analyst

Database Administrator

DevOps EngineerFrontend Engineer

Full Stack Engineer/Developer

Hardware Integration Engineer

Java/.NET DeveloperNetwork Engineer

Product Manager

Program Manager

Project Manager

QA/Test Engineer

Retail Sales Consultant

Security Engineer

Systems Analyst

UX Designer

0.20

0.25

0.30

0.35

0.40

0.45

0.50

0.55

0 200 400 600 800 1000 1200 1400Open Positions

% J

ob

s w

ith

Non

-Deg

ree

Req

uir

em

en

t

Open Positions Analysis - Cambridge

Note: The represented data has been derived using DRAUP Proprietary Talent Module, updated as on Nov, 2018

67

Partnership By Top Peers Across Industries: Companies’ research collaboration is heavily focused on AI/ML

while peer partnerships is across AI, security, computer vision & cloud

AI/MLComputer

Vision/NLPCloud /Security IoT

Research Collaboration Scholarship Start-up Acquisition Corporate Investment Peer-to Peer Partnership

• Apple acquired Cambridge’s voice-recognition spin out VoiceIQ

• Apple is collaborating with the Cambridge to work on ameliorating Siri

• Apple partnered with Microsoft and Amazon on AI research

• ARM funds Simprints that works on application of biometrics

• Geomerics, that specializes in software for calculating radiosity & used in rendering

engines of video games, was acquired by ARM

• Microsoft partnered with Cambridge University for research in Artificial Intelligence.

• It provides support to PhD students & offers post doctoral research position at

Microsoft Research Lab

• Microsoft & Amazon are working on Cortana-Alexa partnership

• Qualcomm acquired CSR, a semiconductor company spun out of Cambridge

• Qualcomm’s Innovation Fellowship supports researchers in AI/ML at Cambridge

university

• Qualcomm is developing voice assistance in wireless headphones in partnership

with Amazon

• Nokia’s Bell Labs is collaborating with Cambridge University to advance AI supported

multisensory personal devices

• Nokia and Cambridge University are co-developing technologies for Morph (flexible

circuitry & nanowire sensing

• AstraZeneca is partnering with Cambridge with focus on visual observations of

molecules behind disease pathways

• AstraZeneca partnered with Microsoft to build business intelligence solutions

• Amazon is collaborating with Cambridge to work on Alexa, core ML and Amazon

devices like Echo smart speakers, Fire tablets, Kindle, etc

• Nokia collaborated with Amazon web services for easier transition to the cloud

Note: The above information is based on data provided by the respective companies and Cambridge University 68

69

Hiring Difficulty Analysis

ParametersTalent Supply

from tier-1 universities

Total Employed

talent

Demand (%Open

Positions)Attrition rate Cost of labor

Maturity of Talent Pool

Overall Difficulty

AI/ML Low Medium High Medium High Medium High

NLPMedium Low Medium High High Low High

Computer

Vision Low Low Medium Medium High Low High

Software

EngineerHigh High High Low Medium Medium Low

Security Low Low Low Low Medium High Medium

UI/UX Low Low High Low Low Medium High

IoT Low Medium Low Low Low High Low

Cloud Low Low High High Medium Medium High

Hiring difficulty analysis Insights

• AI/ML, NLP, Computer Vision: Huge competition exists in term hiring top AI/ML, NLP and Computer Vision talent due to low supply, pushing the cost of talent higher compared to other job families.

• Software Developer: Demand for Software engineers is relatively high, due to existence of many enterprise software companies. University Supply of the talent is relatively high due to multiple computer science courses across universities resulting in lower difficulty to hire software talent.

• Security: Due to the low number of Security related courses in the universities, and low demand for security roles as major MNCs/Start-ups focus on Biotech and AI/ML, Hiring difficulty is Medium.

• UI/UX: Low talent availability and high demand is resulting in higher hiring difficulty for UI/UX Job family

• IOT: Cambridge has a few large semiconductor companies employing mature talent with niche IoT skills. Coupled with low demand has resulted in Low hiring difficulty

• Cloud: High difficulty for cloud talent hiring, due to low supply and high demand, as the demand for the role cuts across industries.

Unfavorable Moderate Favorable

Note: DRAUP’s proprietary analysis69

Source : DRAUP

70

70

https://twitter.com/zinnov

https://twitter.com/zinnov

http://facebook.com/ZinnovManagementConsulting

http://facebook.com/ZinnovManagementConsulting

https://www.linkedin.com/company-beta/30724/

https://www.linkedin.com/company-beta/30724/

https://www.youtube.com/channel/UCgEN1J9L2jTqBOlWsH65w8w

https://www.youtube.com/channel/UCgEN1J9L2jTqBOlWsH65w8w

mailto:[email protected]?subject=How can we help you?

mailto:[email protected]?subject=How can we help you?

CAMBRIDGE TALENT STUDY - Amazon S3...CAMBRIDGE TALENT STUDY Talent Stack of the Job Families...

Documents

Transcript of CAMBRIDGE TALENT STUDY - Amazon S3...CAMBRIDGE TALENT STUDY Talent Stack of the Job Families...