EPSRC Centre for Doctoral Training in Statistics and Operational Research in Partnership with Industry (STOR-i)

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


Lancaster University (LU) proposes a Centre for Doctoral Training (CDT) to develop international research leaders in statistics and operational research (STOR) through a programme in which cutting-edge industrial challenge is the catalyst for methodological advance. Our proposal addresses the priority area 'Statistics for the 21st Century' through research training in cutting-edge modelling and inference for large, complex and novel data structures. It crucially recognises that many contemporary challenges in statistics, including those arising from industry, also engage with constraint, optimisation and decision. The proposal brings together LU's academic strength in STOR (>50FTE) with a distinguished array of highly committed industrial and international academic partners. Our shared vision is a CDT that produces graduates capable of the highest quality research with impact and equipped with an array of leadership and other skills needed for rapid career progression in academia or industry.

The proposal builds on the strengths of an existing EPSRC-funded CDT that has helped change the culture in doctoral training in STOR through an unprecedented level of engagement with industry. The proposal takes the scale and scientific ambition of the Centre to a new level by:
* Recruiting and training 70 students, across 5 cohorts, within a programme drawing on industrial challenge as the catalyst for research of the highest quality;
* Ensuring all students undertake research in partnership with industry: 80% will work on doctoral projects jointly supervised and co-funded by industry; all others will undertake industrial research internships;
* Promoting a culture of reproducible research under the mentorship and guidance of a dedicated Research Software Engineer (industry funded);
* Developing cross-cohort research-clusters to support collaboration on ambitious challenges related to major research programmes;
* Enabling students to participate in flagship research activities at LU and our international academic partners.

The substantial growth in data-driven business and industrial decision-making in recent years has signalled a step change in the demand for doctoral-level STOR expertise and has opened the skills gap further. The current CDT has shown that a cohort-based, industrially engaged programme attracts a diverse range of the very ablest mathematically trained students. Without STOR-i, many of these students would not have considered doctoral study in STOR. We believe that the new CDT will continue to play a pivotal role in meeting the skills gap.

Our training programme is designed to do more than solve a numbers problem. There is an issue of quality as much as there is one of quantity. Our goal is to develop research leaders who can innovate responsibly and secure impact for their work across academic, scientific and industrial boundaries; who can work alongside others with different skills-sets and communicate effectively. An integral component of this is our championing of ED&I. Our external partners are strongly motivated to join us in achieving these outcomes through STOR-i's cohort-based programme. We have little doubt that our graduates will be in great demand across a wide range of sectors, both industrial and academic.

Industry will play a key role in the CDT. Our partners are helping to co-design the programme and will (i) co-fund and co-supervise doctoral projects, (ii) lead a programme of industrial problem-solving days and (iii) play a major role in leadership development and a range of bespoke training. The CDT benefits from the substantial support of 10 new partners (including Morgan Stanley, ONS Data Science Campus, Rolls Royce, Royal Mail, Tesco) and continued support from 5 existing partners (including ATASS, BT, NAG, Shell), with many others expected to contribute.

Planned Impact

This 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 and associated academic communities, (v) UK doctoral students in STOR, and (vi) the CDT students themselves.

Below we outline how each of these communities will realise these benefits:

(i) The UK economy will gain a competitive edge through a significant increase in the supply and diversity of doctoral STOR professionals with the skills required to undertake influential, responsible and impactful research, and who have been trained to become future leaders. Our goal is that our future alumni who enter industry assume leading roles in realising the major impact that STOR can make in achieving effective data driven decision-making. Our existing alumni are already starting to achieve this. A wider societal benefit will accrue from research contributions to EPSRC Prosperity Outcomes, e.g. to the UK being a Productive and Resilient Nation.

(ii) Our industrial partners will particularly benefit from the skills supply identified in item (i), as likely employers of STOR-i graduates. They will 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-supervised with industry, industrial internships, engagement in research clusters and industrial problem-solving days. Our training programme will give students the skills they need to ensure that research is conducted responsibly and that outcomes are successfully communicated to beneficiaries. The value that our industrial partners place on working with STOR-i can be seen through the pledged cash support of £1.7M.

(iii) A wider benefit will accrue from the employment of STOR-i graduates, equipped as described in items (i) and (ii), across non-partner public and private sector organisations. The breadth and depth of training provided by the CDT will enable students to quickly make a difference in these organisations, using their research skills to affect significant change.

(iv) The STOR academic community will benefit from methodological advances and from the increase and diversity in the supply of STOR researchers who value, and have experience of, collaborative research. Our alumni will be leaders in 21st Century Statistics with a strong culture of, and training in, reproducible research and a focus on achieving impact with excellence. Our recruitment strategy will further benefit this community in achieving a healthier supply of high-quality doctoral candidates from diverse backgrounds. Our research internship programme gives top mathematically able individuals from across the UK an experience of STOR research and has been shown to increase applications 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 financial support from our industrial partners, we will continue our National Associate Scheme. This will provide up to 50 UK STOR doctoral students with funding and access to elements of STOR-i's training programme. An annual conference will provide opportunities for learning, networking and sharing research progress to members of the scheme.

(vi) STOR-i students will benefit from a personalised programme that will support each individual in fully achieving their research leadership potential, whether in academia or industry. Students will be given the tools and opportunities to develop research and broader skills that will enable them to achieve maximum scientific impact for their work. Our current alumni provide strong evidence that these future graduates will be extremely employable.


10 25 50

Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/S022252/1 30/09/2019 30/03/2028
2284198 Studentship EP/S022252/1 30/09/2019 29/09/2023 Peter Greenstreet
2284926 Studentship EP/S022252/1 30/09/2019 29/09/2023 Aaditya Bhardwaj
2284949 Studentship EP/S022252/1 30/09/2019 29/09/2023 Eleanor D'Arcy
2284174 Studentship EP/S022252/1 30/09/2019 29/09/2023 George Dewhirst
2284168 Studentship EP/S022252/1 30/09/2019 29/09/2023 Matthew Darlington
2284300 Studentship EP/S022252/1 30/09/2019 29/09/2023 Kes Ward
2284307 Studentship EP/S022252/1 30/09/2019 29/09/2023 Tessa Wilkie
2284124 Studentship EP/S022252/1 30/09/2019 29/04/2024 Elizabeth Daniells
2284260 Studentship EP/S022252/1 30/09/2019 31/03/2024 Matthew Randall
2284954 Studentship EP/S022252/1 30/09/2019 29/09/2023 Tamas Papp
2284258 Studentship EP/S022252/1 30/09/2019 29/09/2023 Edward Mellor
2284969 Studentship EP/S022252/1 30/09/2019 29/09/2023 Hamish Thorburn
2440310 Studentship EP/S022252/1 30/09/2020 29/09/2024 Ziyang Yang
2440228 Studentship EP/S022252/1 30/09/2020 29/09/2021 Martin Dimitrov
2440095 Studentship EP/S022252/1 30/09/2020 29/09/2024 Rebecca Hamm
2438819 Studentship EP/S022252/1 30/09/2020 29/09/2024 Jacob Elman
2440212 Studentship EP/S022252/1 30/09/2020 29/09/2024 Jack Trainer
2440153 Studentship EP/S022252/1 30/09/2020 29/09/2024 Owen Li
2438701 Studentship EP/S022252/1 30/09/2020 29/09/2024 Matthew Davison
2440217 Studentship EP/S022252/1 30/09/2020 29/09/2024 Lidia Branco Correia Martins André
2440241 Studentship EP/S022252/1 30/09/2020 29/09/2024 Robyn Goldsmith
2440162 Studentship EP/S022252/1 30/09/2020 29/09/2024 Maddie Smith
2440139 Studentship EP/S022252/1 30/09/2020 29/04/2025 Katie Howgate
2438812 Studentship EP/S022252/1 30/09/2020 29/09/2024 Daniel Dodd
2440302 Studentship EP/S022252/1 30/09/2020 31/10/2024 Jordan Hood
2440306 Studentship EP/S022252/1 30/09/2020 29/09/2024 Conor Murphy
2605172 Studentship EP/S022252/1 30/09/2021 29/09/2025 Benjamin Lowery
2608246 Studentship EP/S022252/1 30/09/2021 29/09/2025 Connie Trojan
2608270 Studentship EP/S022252/1 30/09/2021 29/09/2025 Nikolaos Tsikouras
2605180 Studentship EP/S022252/1 30/09/2021 29/09/2025 Thomas Newman
2605165 Studentship EP/S022252/1 30/09/2021 29/09/2025 Luke Fairley
2608293 Studentship EP/S022252/1 30/09/2021 29/09/2025 Harini Jayaraman
2608238 Studentship EP/S022252/1 30/09/2021 29/09/2025 Matthew Speers
2605245 Studentship EP/S022252/1 30/09/2021 29/09/2025 Carla Pinkney
2605147 Studentship EP/S022252/1 30/09/2021 29/09/2025 Georgios Aliatimis
2608381 Studentship EP/S022252/1 30/09/2021 29/09/2025 Danielle Notice
2753510 Studentship EP/S022252/1 30/09/2022 29/09/2026 Max Howell
2753259 Studentship EP/S022252/1 30/09/2022 29/09/2026 Adam Page
2753514 Studentship EP/S022252/1 30/09/2022 29/09/2026 Robert Lambert
2753494 Studentship EP/S022252/1 30/09/2022 29/09/2026 James Neill
2753394 Studentship EP/S022252/1 30/09/2022 29/09/2026 Graham Burgess
2753504 Studentship EP/S022252/1 30/09/2022 29/09/2026 Kristina Bratkova
2753579 Studentship EP/S022252/1 30/09/2022 29/09/2026 Wanchen Yue
2753522 Studentship EP/S022252/1 30/09/2022 29/09/2026 Theo Crookes