Introductory description

N/A.

Module web page

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

The dissertation is expected to follow the topic suggested by the Project Supervisor, which will have been approved by the CDT board according to the procedures outlined in the HetSys course description. The dissertation must demonstrate detailed knowledge and approaches the frontiers of research, with the innovative requirement to include explicit quantification of uncertainties and/or modern aspects of software design.

Learning outcomes

By the end of the module, students should be able to:

• Demonstrate knowledge of state-of-the-art practices and methodologies in an area of computational modelling as applied to heterogeneous materials systems, and a wide-ranging understanding of the context of these practices within the broader field.
• Create novel understanding, interpretation and prediction of the behaviour of a complex heterogeneous system through computational modelling, applicable to cutting-edge technology or fundamental research.
• Create or adapt, and then analyse, an appropriate computational model within robust scientific software, including means to acquire quantitative insight into the uncertainty and error bars associated with predictions it makes.
• Communicate of the results of this research to other researchers in related disciplines.
• Be defended in a viva voce examination by internal examiners who are experts in a related field of study.

Research element

Research project within HetSys CDT.

Subject specific skills

Demonstrate knowledge of state-of-the-art practices and methodologies in an area of computational modelling as applied to heterogeneous materials systems, and a wide-ranging understanding of the context of these practices within the broader field.

Create novel understanding, interpretation and prediction of the behaviour of a complex heterogeneous system through computational modelling, applicable to cutting-edge technology or fundamental research.

Create or adapt, and then analyse, an appropriate computational model within robust scientific software, including means to acquire quantitative insight into the uncertainty and error bars associated with predictions it makes.

Communicate of the results of this research to other researchers in related disciplines
be defended in a viva voce examination by internal examiners who are experts in a related field of study.

Transferable skills

Writing and presentation skills. Data Analysis.