EPSRC Centre for Doctoral Training in Collaborative Computational Modelling at the Interface

Started

Other Cross-Cutting Technologies or Research
Not Energy Related

Training

PHYSICAL SCIENCES AND MATHEMATICS (Applied Mathematics)
PHYSICAL SCIENCES AND MATHEMATICS (Computer Science and Informatics)

Not Cross-cutting

Dr T Betcke
Mathematics
University College London

Standard

EPSRC

01 July 2024

30 September 2033

111 months

£8,795,896

Information Technologies

London

EPSRC Training Grants

Dr T Betcke, Mathematics, University College London

Dr MM Betcke, Computer Science, University College London
Dr C Cotter, Mathematics, Imperial College London
Professor SE Guillas, Statistical Science, University College London
Dr DF Kalise Balza, Mathematics, Imperial College London
Dr R Misener, Computing, Imperial College London
Professor H Ni, Mathematics, University College London
Dr V Shahrezaei, Mathematics, Imperial College London

Since the advent of numerical weather prediction in the early twentieth century, physics driven computational modelling has gone from strength to strength, underpinning much of the modern world, from the design of new bridges and buildings that can withstand earthquakes, to the aerodynamic optimisation of airplanes and the simulation of materials for batteries underpinning the electric car revolution. But physics based models alone have limits in what they can do. From high dimensional control problems to multiscale fluid flow, there are many important systems where conventional discretise-and-solve approaches remain permanently out reach. In other important systems, we have no physical models at all (in natural language processing and many other areas). In these data based approaches we have seen tremendous advances over the last decade, exemplified by the deep learning revolution. There is a now a growing consensus that computational models of tomorrow will consist of combinations of physics and data driven approaches and should not be viewed separately from each other.There is one more missing ingredient, attaining increasing recognition by research labs across the world, namely research software engineering. Traditionally seen as a professional service to support the implementation of computational models, research software engineering now emerges as an equal academic pillar to computational mathematics and data driven approaches. Software design, and hardware limitations, inform and shape the design of computational methods. Researchers need to take a holistic view across computational modelling and software engineering to create truly innovative solutions to the truly challenging problems from digital twins in personal medicine to simulating and mitigating the effects of climate change.This CDT has been designed around the need to train graduates across the interfaces of physics and data driven computational modelling and research software engineering. Our trainees will be able to engage with challenging problems not only from a modelling perspective but also from a software perspective, moving fluently across modelling and research software engineering.The subsequent urgent need for training in research software engineering at the highest level is also increasingly recognised by research centres across the world. We have partnered with a number of institutions in this proposal who follow this vision. In the UK this has been recently exemplified by the Independent Review of the Future of Compute, which recognised the importance of pairing infrastructure investments with skills programmes, and the importance of creating, attracting and retaining world class compute talent. Paired with an innovative training programme around interface working groups and software projects, our graduates will participate in and shape world leading research across the mathematics of data enhanced computational modelling, the design of corresponding computational algorithms, scientific research software engineering, and domain specific applications

24/07/24