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Details of Grant 

EPSRC Reference: EP/Y035429/1
Title: EPSRC Centre for Doctoral Training in Modelling of Heterogeneous Systems - HetSys II
Principal Investigator: Kermode, Professor JR
Other Investigators:
Turner, Dr HL Hine, Professor NDM Staunton, Professor JB
Bartok-Partay, Dr LL Jelicic, Ms V Stansfeld, Professor PJ
Figiel, Dr LW Brommer, Dr P Hudson, Dr T
Researcher Co-Investigators:
Project Partners:
Adjacency Group Aix-Marseille University ANSYS
AstraZeneca Atomic Weapons Establishment Beijing Normal University
Ca' Foscari University of Venice Cresset BioMolecular Discovery Ltd Dassault Systemes
Diamond Light Source Discover Materials Fraunhofer Institut (Multiple, Grouped)
Free University of Brussels (VUB) Fujitsu Henry Royce Institute
High Value Manufacturing (HVM) Catapult Innovate UK KTN Isaac Newton Institute
Jaguar Land Rover Limited Johnson Matthey Karlsruhe Institute of Technology (KIT)
Los Alamos National Laboratory Morgan Advanced Materials plc (UK) Nanjing University
Oxford Photovoltaics Limited Pfizer QinetiQ
Research Centre Juelich GmbH (Helmholtz) Ruhr University Bochum Shanghai Jiao Tong University
Syngenta Technical University of Dresden The Falcon Project Ltd
The Faraday Institution Trinity College Dublin TWI Ltd
UK Atomic Energy Authority University of British Columbia (UBC) University of Gothenburg
University of Minnesota University of Stuttgart Waters Corporation
Zenotech Ltd
Department: Sch of Engineering
Organisation: University of Warwick
Scheme: Centre for Doctoral Training
Starts: 01 October 2024 Ends: 31 March 2033 Value (£): 7,299,617
EPSRC Research Topic Classifications:
Materials Characterisation Materials Synthesis & Growth
EPSRC Industrial Sector Classifications:
Healthcare Energy
R&D
Related Grants:
Panel History:
Panel DatePanel NameOutcome
20 Nov 2023 EPSRC Centres for Doctoral Training Interview Panel L November 2023 Announced
Summary on Grant Application Form
Meeting emerging science and engineering modelling challenges requires scientists who can master complex theory and simulation techniques, can assimilate data, and can collaborate in multidisciplinary teams with expertise across a range of modelling scales. Securing the UK's position as a world-leading research hub into the future therefore requires a well-integrated pool of researchers with a skillset that is both broad and deep.

HetSys is leading the way in addressing these needs by producing students with the tools necessary to meet the challenges of the future through our training programme. We are training the scientists who will develop the next generation of computational models, implemented in reusable software with robust error bars from uncertainty quantification (UQ), and who can learn from experimental and simulated data on an equal footing through advances in 'scientific machine-learning' (SciML). Linking heterogeneous materials models with UQ allows performance to be improved, enabling the technology needed to reach net zero through a step-change in design capability. The ongoing AI revolution has necessitated a redesign of our training programme to enable us to build on what we learnt during the first funding period and deliver our new vision. In particular, changes to our core training enable our students to (i) embed robust and sustainable research software engineering (RSE) in modelling; (ii) quantify modelling uncertainties through enhanced use of statistical methods; and (iii) exploit new trends in scientific machine learning.

The research focus of HetSys on new paradigms in the behaviour of heterogeneous materials remains vital for the competitiveness of the UK's high-value manufacturing and automotive industries. Prominent examples of challenges we are addressing include the design of (i) energy materials for future vehicles with reduced carbon footprints; (ii) low dimensional and/or strongly correlated materials for quantum devices; (iii) high entropy alloys for fusion applications; (iv) biomolecules for combatting infectious diseases. Historically, the modelling pattern has focused on just one length- or time-scale; HetSys transforms this landscape by explicitly targeting the multiscale modelling of heterogeneous systems required by industry. The expertise we have accumulated opens up opportunities to capitalise on the transformative combination of mechanistic modelling with data-driven approaches (SciML). This requires a broader combination of disciplinary expertise, provided through our enhanced bespoke training programme.

Only a cohort approach can train high-quality computational scientists who can develop and implement new modelling methods in close collaboration with other scientists. The cohesive, interdepartmental cohorts and training programme we are creating lower many of the current barriers to interdisciplinary work and demonstrate our vision for the future of scientific endeavour, where teams of researchers work together to combine their skills and expertise. Only a critical mass of students and a large and highly collaborative team of supervisors makes this targeted and fully inclusive training approach feasible. HetSys supports the delivery of EPSRC's Physical and Mathematical Sciences Powerhouse strategic priority, helping to provide the platform on which research and innovation across the sciences is built.

Key Findings
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Organisation Website: http://www.warwick.ac.uk