Lead Research Organisation: Lancaster University
Department Name: Mathematics and Statistics


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.

Planned Impact

The proposal will benefit (i) the UK economy and society, (ii) our industrial partners, (iii) the wider community of non-academic employers of doctoral graduates in STOR, (iv) the scientific disciplines of statistics and operational research (STOR) and associated academic communities, (v) UK doctoral students in STOR, and (vi) the CDT students themselves.

(i) The UK economy will gain a competitive edge through a significant increase in the supply of doctoral STOR professionals with the skills to achieve impact for their work, and who have been trained with the goal of becoming future leaders. Our goal is that those of our graduates who enter industry will assume leading roles in realising the major impact which STOR can make in achieving effective data driven decision-making. A wider societal benefit will accrue from research contributions, inter alia, to the EPSRC themes of Energy, Living with Environmental Change and Global Uncertainties.

(ii) Many of our industrial partners will benefit from the skills supply identified in (i), as likely future employers of STOR-i graduates. They further benefit from teaming with a community of leading edge STOR researchers in the solution of substantive industrial challenges. Mechanisms for the latter include doctoral projects co-funded by and co-supervised with industry, industrial internships and industrial problem-solving days. Our training programme will give students the skills they need to make sure that research outcomes are successfully communicated to beneficiaries. The value that our industrial partners place on working with STOR-i can be seen in over £5M of pledged support.

(iii) A wider benefit will accrue from the employment of STOR-i graduates, equipped as described in (i), across non-partner industrial, government and public sectors organisations. These will also benefit from the networking opportunities afforded by access to STOR-i events and from the dissemination of research outcomes accessibly within nonacademic communities.

(iv) The STOR academic community will benefit from methodological advances and from the increase in supply of STOR researchers who value and have experience of collaborative research. Our recruitment strategy will further benefit this community in achieving a healthier supply of high quality doctoral candidates beyond STOR-i: our research intern programme gives top undergraduates from across the UK an experience of STOR research while STOR-i recruitment roadshows partner with the STOR community of the hosting institution. Experience with the current Centre has shown that both of these lead to an increase in applicants for STOR PhD programmes across the UK.

(v) Elements of the STOR-i programme will benefit the wider community of UK doctoral students in STOR. Using the financial support of our external partners, we will develop a STOR-i national associate scheme for UK STOR doctoral students working with industry. This will give funding and access to elements of the STOR-i training programme while an annual event will provide opportunities for learning, networking and sharing research progress to members of the scheme.

(vi) The STOR-i students will benefit from a programme which will support their growth toward research leadership, whether in academia or industry. They will be challenged to achieve their maximum scientific potential and also given the tools and opportunities to develop the broader skills which will enable them to achieve maximum scientific impact. They will be highly employable.


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