HetSys is an EPSRC-supported Centre for Doctoral Training. It recruits enthusiastic students from across the physical sciences who enjoy using their mathematical skills and thinking flexibly to solve complex problems.

By developing these skills HetSys will train you to challenge current state-of-the-art in computational modelling of heterogeneous ‘real world’ systems across a range of research themes such as nanoscale devices new catalysts superalloys smart fluids laser-plasma interactions etc.

Course Overview

The HetSys training programme addresses three key training needs:

Span disciplinary barriers. The most challenging real-world heterogeneous systems are intrinsically multidisciplinary requiring integration of a diverse range of modelling methods.
Incorporate uncertainty in modelling. Training in uncertainty quantification will enable students not only to perform simulations but also to quantitatively assess their reliability.
Promote robust Research Software Engineering (RSE). Training in sustainable software development will enhance software usability and extend its lifetime.

Research Themes

Examples of areas of current research within the remit of the HetSys CDT include the following themes. Please see our projects page for specific projects currently being advertised.

• Novel electronic devices
• Catalysis across scales
• High-performance alloys
• Direct-drive laser fusion
• Heterogeneous modelling for future medicines
• Smart nanofluidic interfaces
• Composite materials with enhanced functionality
• Heterogeneity of underground systems
• Mathematical challenges
• Simulation optimisation

Teaching and Learning

HetSys' training programme is designed to enable you to become a high-quality computational scientist who is comfortable working in interdisciplinary environments has excellent communication skills and is well prepared for a wide range of future careers in areas where there is demonstrable need.

During the first 18 months of the programme you will study four core modules (Multiscale Modelling Methods and Applications I and II Research Computing/Software Carpentry and Predictive Modelling and Uncertainty Quantification) and at least two optional modules participate in a Group Software Development Project supported by academics and RSEs and carry out an independent research project in the area of the PhD project assessed through a written report and viva 12 months into the programme.