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EPSRC CDT in Modelling of Heterogeneous Systems - HetSys

People

HetSys CDT - an EPSRC supported Centre for Doctoral Training

We recruit students from across the physical sciences who enjoy using their mathematical skills and thinking flexibly to solve complex problems.

By developing these skills HetSys trains people to challenge current state-of-the-art in computational modelling of heterogeneous, ‘real world’ systems across a range of research themes

HetSys is built around a closely knit, highly collaborative team of academics from five science departments at Warwick with a strong track record in leading large projects.

With its project partners HetSys develops talented, energetic PhD students to push boundaries in this exciting field. The students have the potential to inspire new ideas, approaches and innovation and become future leaders in developing new technologies.

HetSys builds on Warwick’s cross-departmental scientific computing research community and the Warwick Centre for Predictive Modelling (WCPM).

Read more about the HetSys training programme and have a look at our available PhD Projects and how to apply.

Information for Prospective Supervisors

We have an open call each year (around September/October) for projects that fit the remit of our CDT.

There is a proposal form for new projects where supervisors are asked to describe the project and its fit to HetSys and the extent to which it requires and builds on the HetSys training, which is a key requirement for all projects.

Projects which attract industry co-funding are significantly prioritised as long as they are within our remit, while 100% EPSRC-funded projects are scored based on the fit to HetSys supervisor's contribution to the CDT delivery (delivery of training, industry engagement etc). PhD projects should align with from HetSys’ training objectives which are to:

  1. Embed a culture of robust and sustainable RSE in modelling, to enhance software usability, extend its lifetime and increase its reliability.
  2. Quantify modelling uncertainties. Promote and expand the use of UQ, enabling students not only to perform simulations, but also to quantitatively assess their reliability.
  3. Exploit new trends in Scientific Machine Learning (SciML), combining mechanistic & data-driven approaches.

Because this is the focus of our training, most projects are aligned with materials, molecular, fluids or plasma simulation across a range of length and time scales.

If you want to be added to our open call mailing list please email hetsys@warwick.ac.uk