Projects
Projects: Projects for Investigator |
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| Reference Number | EP/Y035429/1 | |
| Title | EPSRC Centre for Doctoral Training in Modelling of Heterogeneous Systems - HetSys II | |
| Status | Started | |
| Energy Categories | Other Cross-Cutting Technologies or Research 20%; Not Energy Related 80%; |
|
| Research Types | Training 100% | |
| Science and Technology Fields | PHYSICAL SCIENCES AND MATHEMATICS (Metallurgy and Materials) 50%; PHYSICAL SCIENCES AND MATHEMATICS (Computer Science and Informatics) 50%; |
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| UKERC Cross Cutting Characterisation | Not Cross-cutting 100% | |
| Principal Investigator |
Dr J R Kermode No email address given School of Engineering University of Warwick |
|
| Award Type | Standard | |
| Funding Source | EPSRC | |
| Start Date | 01 October 2024 | |
| End Date | 31 March 2033 | |
| Duration | 102 months | |
| Total Grant Value | £7,299,617 | |
| Industrial Sectors | Energy; Healthcare; R&D | |
| Region | West Midlands | |
| Programme | EPSRC Training Grants | |
| Investigators | Principal Investigator | Dr J R Kermode , School of Engineering, University of Warwick (99.991%) |
| Other Investigator | Dr P Brommer , School of Engineering, University of Warwick (0.001%) Ms V Jelicic , School of Engineering, University of Warwick (0.001%) Dr LL Bartok-Partay , Chemistry, University of Warwick (0.001%) Professor JB Staunton , Physics, University of Warwick (0.001%) Professor NDM Hine , Physics, University of Warwick (0.001%) Dr LW Figiel , Warwick Manufacturing Group, University of Warwick (0.001%) Professor PJ Stansfeld , School of Life Sciences, University of Warwick (0.001%) Dr HL Turner , Statistics, University of Warwick (0.001%) Dr T Hudson , Mathematics, University of Warwick (0.001%) |
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| Web Site | ||
| Objectives | ||
| Abstract | 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 ofresearchers 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. | |
| Data | No related datasets |
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| Projects | No related projects |
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| Publications | No related publications |
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| Added to Database | 05/06/24 | |
