Scientific Computing

Study mode:On campus Study type:Full-time Languages: English
Local:$ 29.2 k / Year(s) Foreign:$ 49.1 k / Year(s) Deadline: Jun 29, 2025
6 place StudyQA ranking:2733 Duration:1 year

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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 the 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 they will undertake a substantial Research Project over the next 6 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%; written assignments on the core courses 25%; written examinations on the elective courses 25%.

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;
  • 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 or greater than 75%).

The taught element comprises core lecture courses on topics of all aspects of scientific computing, and elective lecture courses relevant to the topic of 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%; written assignments 25%; written examinations 25%.

The core lectures are on topics of high performance scientific computing numerical analysis and advanced numerical methods and techniques. They are organized by the Centre for Scientific Computing and are taught and examined during the first five months (October-February). Their purpose is to provide the students with essential background knowledge for completing their dissertation and for their general education in scientific computing.

In particular, their objective is to introduce students to the simulation science pipeline of problem identification, modelling, simulation and evaluation - all from the perspective of employing high-performance computing (HPC). Numerical discretisation of mathematical models will be a priority, with a specific emphasis on understanding the trade-offs (in terms of modelling time, pre-processing time, computational time, and post-processing time) that must be made when solving realistic science and engineering problems. Understanding and working with computational methods and parallel computing will be a high priority. To help the students understand the material, the lecturers will furnish the courses with practical coursework assignments.

The lectures on topics of numerical analysis and HPC are complemented with hands-on practicals using Linux-based laptops provided by the course (students may bring their own), as well as on the University’s High Performance Computing Service.

Appropriate elective lecture courses are selected from Master’s-level courses offered by the Departments of the School of Physical Sciences, Technology or Biological Sciences. The choice of courses will be such as to provide the students with essential background knowledge for completing their theses and for their general education in the materials science application of the project. They are decided in consultation with the project supervisor. While every effort is made within the Departments to arrange the timetable in a coherent fashion, it is inevitable that some combinations of courses will be ruled out by their schedule, particularly if the choices span more than one department.

   
One to one supervision

Students are under the general direction of the course director. Each student is assigned a research project supervisor who guides the student's choice of courses and responds to the student's requests for supervisory guidance.

The University of Cambridge publishes an annual Code of Practice which sets out the University’s expectations regarding supervision.

Seminars & classes

The course has a seminar programme which invites academic and industrial speakers. The students also give presentations of their research work as a preparation for their mid-term assessment.

Lectures

Students attend at least 72 hours of lectures in (for example) scientific high performance computing and numerical analysis, as well as lectures from other Master’s level courses across the University, on topics related to their research project.

Practicals

The lectures on topics of numerical analysis and HPC are complemented with hands-on practicals on local computers as well as on the University’s High Performance Computing Service.

Small group teaching

Small group teaching ("supervisions") are offered on the four numerical analysis lecture courses, these include both one-to-one and group supervisions.

Literature_reviews

Literature reviews are part of the two written assignments and of the research project dissertation.

Posters

The students have to give presentations on their research project as part of their mid-term assessment and have to present a poster at their viva-voce examinations.

Feedback

Feedback on the student’s performance on their examination and on the written assignment results is provided by the course Director; feedback on their research project progress is provided by their research project supervisor. Students receive written termly progress reports.

Graduate students are represented on the Department's Graduate Student Consultative Committee, which normally meets five times a year, and consists of one or more student representatives from each of the research groups. The Committee exists to enable discussion of any issue affecting graduate students and students may approach any member of the Committee to suggest items for discussion.

Assessment

Thesis

The topic of the project (and hence the choice of supervisor) should fall within the research interests of the groups within the Departments of the Schools of Physical Sciences, Technology and Biological Sciences. The project is supervised by a member of the research groups of the Departments of the School. To gain examination credit for the research element, (50% credit towards the degree), students have to submit by the end of August a 15,000-word (maximum) dissertation on a substantial project of original research. The viva voce examination of the dissertation will take place during September, conducted by two examiners (an external examiner from another institution and an internal examiner, who cannot be the student’s supervisor or anyone closely associated with the supervision process) and carried out according to the relevant University regulations. The assessment of the projects is based on the candidate's understanding of the background literature, the commitment of the candidate to the project, the degree of originality shown in the research and the degree of rigour applied in justifying any conclusions.

Essays

The taught element is examined in part by means of two written assignments amounting to 6 credit units. Together with the written examination papers (see the relevant section), the students must accumulate a total of 12 units for examination credit (24 hrs course = 4 units, 16 hrs course = 2.5 units, 12 hrs course = 2 units, 6 hrs course = 1 unit).

Written examination

The taught element is examined in part by means of unseen written examination papers also amounting to 6 credit units. Together with the two written assignments, the students must accumulate a total of 12 units for examination credit (24 hrs course = 4 units, 16 hrs course = 2.5 units, 12 hrs course = 2 units, 6 hrs course = 1 unit).

  • Magistr (Master's Degree) at Pass level. Diploma Specialista (completed post-1991) with a minimum overall grade of good or 4/5 Bachelor's from Moscow Institute of Physics and Technology and other prestigious institutions with an overall grade of 4/5 Bologna Bachelor's from other institutions with an overall grade of 5/5, Excellent
  • Diploma Specialista (completed post-1991) with a minimum overall grade of Excellent or 5/5 Bachelor's from Moscow Institute of Physics and Technology and other prestigious institutions with an overall grade of 5/5
  • IELTS (Academic) 7.0
  • TOEFL Internet Score 100
  • £50 application fee
  • First Academic Reference
  • Second Academic Reference
  • Transcript
  • Personal Reference. 

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