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Details of Grant 

EPSRC Reference: EP/L015692/1
Title: EPSRC CENTRE FOR DOCTORAL TRAINING IN STATISTICS & OPERATIONAL RESEARCH IN PARTNERSHIP WITH INDUSTRY (STOR-i)
Principal Investigator: Tawn, Professor J
Other Investigators:
Glazebrook, Professor KD Eckley, Professor IA
Researcher Co-Investigators:
Project Partners:
AstraZeneca ATASS Ltd BT
Defence Science & Tech Lab DSTL IBM JBA Trust
marketingQED National Nuclear Laboratory Naval Postgraduate School
Northwestern University Numerical Algorithms Group Ltd Perceptive Engineering Ltd
SAS Software Limited Scottish and Southern Energy (SSE) Shell
Smith Institute University of Oslo University of Washington
Winton Capital Management Ltd.
Department: Mathematics and Statistics
Organisation: Lancaster University
Scheme: Centre for Doctoral Training
Starts: 01 April 2014 Ends: 30 September 2022 Value (£): 3,878,130
EPSRC Research Topic Classifications:
Mathematical Aspects of OR Statistics & Appl. Probability
EPSRC Industrial Sector Classifications:
Information Technologies Sports and Recreation
Communications Environment
Financial Services Pharmaceuticals and Biotechnology
Energy
Related Grants:
Panel History:
Panel DatePanel NameOutcome
23 Oct 2013 EPSRC CDT 2013 Interviews Panel D Announced
Summary on Grant Application Form
Lancaster University (LU) proposes a Centre for Doctoral Training (CDT) whose goal is the development of international research leaders in statistics and operational research (STOR) through a programme in which industrial challenge is the catalyst for methodological advance. The proposal brings together LU's considerable academic strength in STOR with a formidable array of external partners, both academic and industrial. All are committed to the development of graduates capable of either leadership roles in industry or of taking their experience of and commitment to industrial engagement into academic leadership in STOR.

The proposal develops an existing EPSRC-funded CDT (STOR-i) by a significant evolution of its mission which takes its degree of industrial engagement to a new level. This considerably enhanced engagement will further strengthen STOR-i's cohort-based training and will result in a minimum of 80% of students undertaking doctoral projects joint with industry, up from 50% in the current Centre. Industrial internships will be provided for those not following a PhD with industry. Industry will (i) play a role in steering the Centre, (ii) has co-designed the training programme, (iii) will co-fund and co-supervise industrial doctoral projects, (iv) will lead a programme of industrial problem-solving days and (v) will play a major role in the Centre's programme of leadership development. Industry's financial backing is providing for stipend enhancement and a range of infrastructure and training support as well as helping to bring STOR-i benefits to a wide audience. The total pledged support for STOR-i is over £5M (including £1.1M cash).

The proposal addresses the priority area 'Industrially-Focussed Mathematical Modelling'. Within this theme we specifically target 'Statistics' (itself a priority area) and Operational Research (OR). This choice is motivated first by the pervasive need for STOR solutions within modern industrial problems and second by theidely acknowledged and long standing skills-shortage at doctoral level in these areas. Our partners' statements of support attest that the substantial recent growth in data acquisition and data-driven business and industrial decision-making have signalled a step change in the demand for high level STOR expertise and have opened the skills gap still wider. The current Centre has demonstrated that a high quality, industrially engaged programme of research training can create a high demand for places among the very ablest mathematically trained students, including many who would otherwise not have considered doctoral study in STOR. We believe that the new Centre will play a yet more strategic role than its predecessor in meeting the persistent skills gap.

Our training programme is designed to do more than solve a numbers problem. There is an issue of quality of graduating doctoral students in STOR as much as there is one of quantity. Our goal is to develop research leaders who are able to secure impact for their work across academic, scientific and industrial boundaries; who can work alongside others who are differently skilled and who can communicate widely. Our external partners are strongly motivated to join us in achieving this through STOR-i's cohort-based training programme. We have little doubt that our graduates will be in great demand across a wide range of sectors, both industral and academic.

The need for a Centre to deliver the training resides primarily in its guarantee of a critical mass of outstanding students. This firstly enables us to design a training programme around student cohorts in which peer to peer learning is a major feature. Second, we are able to attract and integrate the high quality contributions (both internal and external to LU) we need to create a programme of quality, scope and ambition.
Key Findings
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Potential use in non-academic contexts
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Organisation Website: http://www.lancs.ac.uk