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Taught Courses

We currently offer three taught MSc degrees: Mathematical Sciences; Particles, Strings and Cosmology; and Scientific Computing and Data Analysis.  Each of these offers a gateway to a variety of careers in the public and private sectors, and a natural pathway to a PhD.

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Some information about the courses is below:

MSc Mathematical Sciences

This programme covers three areas of mathematical study: Pure Mathematics, Probability and Statistics, and Applications of Mathematics.  Students select 6 modules, from about 30 across those areas, for 8 months of taught study.  They then sit written exams and produce a dissertation on a topic within the research field of one of our academic staff (who have a broad range of interests).

MSc Particles, Strings and Cosmology

This course is a rigorous one-year program that offers a springboard for a PhD in Theoretical Particle Physics within the Centre for Particle Theory.

The Centre for Particle Theory is a combined research group in the Mathematics and Physics Departments forming one of the largest particle theory groups in the UK. Both departments accept students for the M.Sc. degrees. Students receive a thorough training in theoretical high-energy physics through a mixture of formal lectures and personal supervision.

Students interested in the above two courses who are applying from a low or middle-income country may be eligible for the Global Masters Scholarship in Mathematical Sciences

MSc Scientific Computing and Data Analysis

Advances in many fields from science, engineering and economy will be driven by those skilled in handling large parallel machines and data sets with extreme volume or velocity. The Durham MSc in Scientific Computing and Data Analysis (MISCADA) trains students in these areas, equips them with essential professional, entrepreneurial and collaborative skills, and gives them the opportunity to apply all acquired knowledge to challenging, state-of-the-art problems from a computational specialisation area.

The programme is for those with excellent technical skills (in particular mathematics and programming).  It enables students to develop an understanding of how modern scientific computing and data analysis tools work, and to apply the latest data analysis and simulation technologies to their own specialism – whether for an employer, or in pursuit of a PhD.