项目介绍

2021年8月6日

This four-year Doctoral Training Programme on computational methods for material modelling aims to train scientists not only in the use of existing modelling methods but also in the underlying computational and mathematical techniques. This will allow students to develop and enhance existing methods, for instance by introducing new capabilities and functionalities, and also to create innovative new software tools for materials modelling in industrial and academic research.

The first year of the doctoral training programme is provided by the existing MPhil course in Scientific Computing, which has research and taught elements, as well as additional training elements.

The MPhil in Scientific Computing is administered by the Department of Physics, but it serves the training needs of the Schools of Physical Sciences, Technology and Biological Sciences. The ability to have a single master’s course for such a broad range of disciplines and applications is achieved by offering core (ie common for all students) numerical and high-performance computing (HPC) lecture courses, and complementing them with elective courses relevant to the specific discipline applications.

In this way, it is possible to generate a bespoke training portfolio for each student without losing the benefits of a cohort training approach. This bespoke course is fully flexible in allowing each student to liaise with their academic or industrial supervisor to choose a study area of mutual interest.

The final three years consist of a PhD research project, with a student-led choice of projects from a large pool contributed by researchers associated with the CDT. Visit the Projects and Supervisors page on the Centre for Scientific Computing website for more details.

Based on their first-year training and subject to the outcome of examinations, students will then choose a research project to continue a PhD from the start of the second year. This project may be based on the same topic as the preceding placement or project, or it may be different.

Learning Outcomes

By the end of the MPhil, students will have:

• a comprehensive understanding of numerical methods, and a thorough knowledge of the literature, applicable to their own research;
• demonstrated originality in the application of knowledge, together with a practical understanding of how research and enquiry are used to create and interpret knowledge in their field;
• shown abilities in the critical evaluation of current research and research techniques and methodologies; and
• demonstrated self-direction and originality in tackling and solving problems, and acted autonomously in the planning and implementation of research.

By the end of the PhD programme, students will have demonstrated:

• the creation and interpretation of new knowledge, through original research or other advanced scholarship, of a quality to satisfy peer review, extend the forefront of the discipline, and merit publication;
• a systematic acquisition and understanding of a substantial body of knowledge which is at the forefront of an academic discipline or area of professional practice;
• the general ability to conceptualise, design and implement a project for the generation of new knowledge, applications or understanding at the forefront of the discipline, and to adjust the project design in the light of unforeseen problems;
• a detailed understanding of applicable techniques for research and advanced academic enquiry; and
• the development of a PhD thesis for examination that they can defend in an oral examination and, if successful, graduate with a PhD.

Continuing

Distinction (iean average grade greater than 75%) in the MPhil will guarantee admission to the PhD programme. A grade of between 60 and 74% will lead to a review by the CDT Academic Committee on a case-by-case basis. Grades less than 60% will not normally qualify for the PhD programme.

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