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Details of Grant 

EPSRC Reference: EP/L016427/1
Title: EPSRC Centre for Doctoral Training in Data Science
Principal Investigator: Storkey, Professor AJ
Other Investigators:
Goddard, Dr N Buneman, Professor OP Moore, Professor J
Researcher Co-Investigators:
Project Partners:
Agilent Technologies Ltd AlertMe Amazon
Amor Group Apple, Inc. BBC
Biomathematics and Statistics Scotland BrightSolid Online Innovation Carnegie Mellon University
Carnego Systems Limited Center for Math and Computer Sci CWI City of Edinburgh Council
Cloudsoft Corporation Digital Catapult Digital Curation Centre
Freescale Semiconductor Google Helsinki Institute for Information Techn
HSBC IBM UK Ltd IDIAP Research Institute
IST Austria (Institute of Sci & Tech) Leonardo UK ltd Massachusetts Institute of Technology
Microsoft Open Data Institute (ODI) Oracle Corporation
Pharmatics Ltd PRECISE Center, University of Pennsylvan Psymetrix Limited
Quorate Technology Limited Rangespan Ltd Royal Bank of Scotland
Saarland University Scottish Power SICSA
Skyscanner The James Hutton Institute TimeOut
TU Berlin UCB Celltech (UCB Pharma S.A.) UK University of Texas at Austin
University of Washington Xerox Yahoo! Labs
Department: Sch of Informatics
Organisation: University of Edinburgh
Scheme: Centre for Doctoral Training
Starts: 01 April 2014 Ends: 29 February 2024 Value (£): 4,746,532
EPSRC Research Topic Classifications:
Artificial Intelligence Fundamentals of Computing
Information & Knowledge Mgmt
EPSRC Industrial Sector Classifications:
Information Technologies
Related Grants:
Panel History:
Panel DatePanel NameOutcome
23 Oct 2013 EPSRC CDT 2013 Interviews Panel J Announced
Summary on Grant Application Form
Overview: We propose a Centre for Doctoral Training in Data Science. Data science is an emerging discipline that combines machine learning, databases, and other research areas in order to generate new knowledge from complex data. Interest in data science is exploding in industry and the public sector, both in the UK and internationally. Students from the Centre will be well prepared to work on tough problems involving large-scale unstructured and semistructured data, which are increasingly arising across a wide variety of application areas.

Skills need: There is a significant industrial need for students who are well trained in data science. Skilled data scientists are in high demand. A report by McKinsey Global Institute cites a shortage of up to 190,000 qualified data scientists in the US; the situation in the UK is likely to be similar. A 2012 report in the Harvard Business Review concludes: "Indeed the shortage of data scientists is becoming a serious constraint in some sectors." A report on the Nature web site cited an astonishing 15,000% increase in job postings for data scientists in a single year, from 2011 to 2012. Many of our industrial partners (see letters of support) have expressed a pressing need to hire in data science.

Training approach: We will train students using a rigorous and innovative four-year programme that is designed not only to train students in performing cutting-edge research but also to foster interdisciplinary interactions between students and to build students' practical expertise by interacting with a wide consortium of partners. The first year of the programme combines taught coursework and a sequence of small research projects. Taught coursework will include courses in machine learning, databases, and other research areas. Years 2-4 of the programme will consist primarily of an intensive PhD-level research project. The programme will provide students with breadth throughout the interdisciplinary scope of data science, depth in a specialist area, training in leadership and communication skills, and appreciation for practical issues in applied data science. All students will receive individual supervision from at least two members of Centre staff. The training programme will be especially characterized by opportunities for combining theory and practice, and for student-led and peer-to-peer learning.

Key Findings
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Potential use in non-academic contexts
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Date Materialised
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Organisation Website: http://www.ed.ac.uk