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Graduate Admissions

The MPhil programme in Scientific Computing is based in the Department of Physics and is a full-time 12-month course which aims to provide education of the highest quality at master’s level. Covering topics of high-performance scientific computing and advanced numerical methods and techniques, it produces graduates with rigorous research and analytical skills, who are well equipped to proceed to doctoral research or directly into employment in industry, the professions, and public service. It also provides training for the academic researchers and teachers of the future, encouraging the pursuit of research in computational methods for science and technology disciplines, thus being an important gateway for entering PhD programmes containing a substantial component of computational modelling.

The MPhil in Scientific Computing has a research and a taught element. The research element is a project on a science or technology topic which is studied by means of scientific computation. The taught element comprises of core lecture courses on topics of scientific computing and elective lecture courses relevant to the science or technology topic of the project. Most of the projects are expected to make use of the University’s High-Performance Computing Service.

The students will attend lecture courses during Michaelmas term (some courses may be during Lent term) and then undertake a substantial research project over the following six months (from March to the end of August) in a participating department. The research element aims to provide essential skills for continuation to a PhD programme or employment, as well as to assess and enhance the research capacity of the students. It is based on a science or technology topic which is studied by means of scientific computation. Research project topics will be provided by academic supervisors or by the industrial partners who are working with the participating departments and may be sponsoring the research project.

There is equal examination credit weighting between the taught and the research elements of the course, which is gained by submitting a dissertation on the project and by written assignments and examinations on the core and elective courses, respectively.

Weighting of the assessed course components is as follows: dissertation (research) 50 per cent; written assignments on the core courses 25 per cent; and written examinations on the elective courses 25 per cent.

Learning Outcomes

By the end of the course, 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.

Continuing

For continuation to a PhD programme in Scientific Computing, students are required to gain a distinction (overall grade equal to or greater than 75 per cent).


Departments

This course is advertised in the following departments:

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Key Information


12 months full-time

Master of Philosophy

This course is advertised in multiple departments. Please see the Overview tab for more details.

Enquiries

Course on Department Website

Dates and deadlines:

Michaelmas 2018

Applications open
Sept. 4, 2017
Application deadline
June 30, 2018
Course Starts
Oct. 1, 2018

Some courses can close early. See the Deadlines page for guidance on when to apply.

Graduate Funding Competition
Jan. 4, 2018
Gates Cambridge US round only
Oct. 11, 2017

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