The Department of Computer Science at Durham University is pleased to offer a fully funded PhD studentship. The successful applicant will be based in the Department of Computer Science of Durham University – ranked 5th for Computer Science in the UK The Complete University Guide. Durham University is one of the world’s top universities, ranked 78th in QS World University Rankings 2020. We are home to some of the most talented scholars and researchers from around the world who are tackling global issues and making a difference to people’s lives. The project will take place in collaboration with colleagues in the Department of Mathematics at the University of Heidelberg and with industry partners. The successful applicant will have the possibility of research stays at the collaborating institutions during the project.
Many processes and materials in science and engineering are affected by uncertainty, for example due to incomplete information or measurement errors. The importance of capturing these uncertainties cannot be overstated, since overlooking an unlikely yet dangerous scenario could easily have fatal consequences. Numerical simulation of such processes therefore has to address these uncertainties.
Currently, it is usually necessary to couple Uncertainty Quantification (UQ) software and simulation software invasively. This clearly introduces significant technical complexity. Instead this PhD project will work on separating both sides by using a new standardized network interface inspired by microservice architectures. The project will extend UM-Bridge, an open source, community project that provides reference problems for benchmarking of UQ algorithms. The models will be run primarily with GKE in order to provide easy access to High Performance Computing resources without the technical burden (regarding dependencies, compiler versions etc.) traditionally coming with HPC environments. Access to Durham University HPC systems will also be provided.
For entry to the PhD you will be required to have achieved a 2:1 Bachelor’s degree in an appropriate subject, from a recognised university (or equivalent). Strong programming ability and a competent mathematical background are essential. Prior experience in mathematical modeling or uncertainty quantification is beneficial although not essential.
How to apply:
Applicants are encouraged to make enquiries directly to Dr Anne Reinarz anne.k.reinarz(at)durham.ac.uk, https://www.durham.ac.uk/staff/anne-k-reinarz/