Queen Mary University of London DTP Mobility Pilot 2020 2023

Lead Research Organisation: Queen Mary University of London
Department Name: Physics

Abstract

Queen Mary University of London (QMUL) proposes a highly innovative doctoral mobility programme to expand the number of scientists and engineers with data-science and engineering research skills in the UK economy. We will achieve this by widening access routes and increase the diversity of our Doctoral-Scholars. They will be trained to work seamlessly across academic and industrial sectors, and will qualify with professional doctorates. They will benefit from a high-quality bespoke training programme with access to world-class researchers and facilities, and the direct workplace based application of research methods in the live industrial settings of our partners including IBM, BT and the BBC. Data Science skills are in demand and include advanced statistical analysis of large datasets, and the use of artificial intelligence (AI) techniques. The engineering sector also has high demand for skills in modelling and manufacturing engineering, for example. Our programme will expand the provision of skills which now underpin many areas of science and engineering research activity as well as industrial and third-sector innovation. We will provide a sponsorship model to organisations with employed professionals who will be upskilled in data-science and engineering research fields. They will be trained and co-supervised in workplace based research by academics while remaining employed - our Professional Doctoral Scholars. However this model is not suitable for SMEs which typically do not have cash-flows to support such large-scale investment. SMEs will benefit by offering industrial research placements to our Enterprise Doctoral Scholars - talented graduates who left higher education due to financial barriers or other circumstances. They will receive enhanced stipends reducing financial barriers, and be upskilled through our training programme. Placements will allow them to apply their skills in academic and industrial research environments. A new holistic recruitment approach will be used to identify the applicants with the highest potential. Tower Hamlets local authority supports this pilot programme which furthers its aim of enhancing local skills, and expanding the Knowledge Quarter around the high-tech SMEs located in TechCity. This pilot naturally ties together our proven ability in five key areas. (1) Our science and engineering research is world leading and internationally excellent with 90% of our output classified as such [REF2014]. (2) Our strength in doctoral training provision is evidenced by the number of prestigious doctoral training centres, partnerships and EU training networks we host - all strongly supported by an institution-wide Doctoral College. (3) The range of our industrial partnerships is highly recognised, most recently through the £28m award of an Institute of Technology led by QMUL with 30 industry partners. (4) We are a UK leader in widening the participation of people engaging in top-tier higher education by almost any measure. (5) QMUL is an innovator in attracting people from non-academic backgrounds, and was one of the first UK institutions to offer industry-facing degree-apprenticeships, most recently recruiting 25 to its Level 7 programmes and 42 to its Level 6 programmes. This doctoral mobility programme offers a novel, enriched and integrated experience in applied research to train a new class of researcher, adept at working in academic and industrial environments, and enabled with an enviable professional peer-network to draw on throughout their careers. This pilot builds in a comprehensive evaluation framework and a route to disseminate outcomes to stakeholders in UKRI, and graduate education. The future sustainability of this pilot will be through developing doctoral-level apprenticeships, funded by the apprenticeship levy paid by employers to develop vocational skills.

Publications

10 25 50

Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/V519935/1 30/09/2020 29/04/2028
2496675 Studentship EP/V519935/1 01/01/2021 29/09/2026 David Carun
2496680 Studentship EP/V519935/1 18/01/2021 17/01/2028 Ashish Patel
2496930 Studentship EP/V519935/1 19/01/2021 18/01/2025 James Henderson
2496923 Studentship EP/V519935/1 19/01/2021 17/09/2025 Joe Lawton
2496726 Studentship EP/V519935/1 19/01/2021 18/01/2028 Marvin Taylor
2496737 Studentship EP/V519935/1 08/02/2021 07/02/2025 Sibi Catley-Chandar
2604130 Studentship EP/V519935/1 30/09/2021 29/09/2025 Yemisi Oyeleke
2601245 Studentship EP/V519935/1 30/09/2021 29/09/2025 Zimpi Komo
2600177 Studentship EP/V519935/1 30/09/2021 29/09/2027 Caitlin Woods
2604208 Studentship EP/V519935/1 30/09/2021 29/09/2025 Dimitrios Gousis
2603217 Studentship EP/V519935/1 30/09/2021 29/09/2025 George Wright
2603305 Studentship EP/V519935/1 30/09/2021 29/06/2026 Peter Lock
2601988 Studentship EP/V519935/1 30/09/2021 29/09/2025 Aaron Smiles
2603414 Studentship EP/V519935/1 30/09/2021 29/06/2026 Pryanka Vertesi
2601315 Studentship EP/V519935/1 30/09/2021 30/03/2026 Nadeem Khondokar
2603428 Studentship EP/V519935/1 30/09/2021 29/09/2025 Kishan Sthankiya
2751285 Studentship EP/V519935/1 30/09/2022 29/09/2026 Daniel Trussler
2751317 Studentship EP/V519935/1 30/09/2022 29/09/2026 Jane John-Lewis