Special Topics

There is a great variety of special topic lecture courses listed below. Each falls under a broad heading of Modelling, Computation or Other, and is marked [M], [C] or [O] accordingly. Students should complete at least one Modelling course marked [M] in the list and one Computation course marked [C] in the list. A special topic is usually assessed by a mini-project of up to 20 pages on a topic agreed with the lecturer as described in the PDF icon special topic guidelines. Students wishing to do a special topic on one of these courses should inform the lecturer before the end of term, and the special topic must be handed in with a completed PDF icon declaration form by Monday of week 1 of HT for MT lecture courses, by Monday of week 1 of TT for HT lecture courses and by Monday of week 11 of TT for TT lecture courses. The lecturer and one other assessor will mark the work and make a recommendation to the examiners.

It is also possible to do other topics if approved by the M.Sc. Supervisory Committee. Students who wish to follow a lecture course not on the list or to do a special topic based on a reading course should submit a short description of the project to the course director.

These are the courses available for the Academic year 2017-2018. Note that the list of courses may change from year to year.

Michaelmas Term 2017

Hilary Term 2018

  • Applied Complex Variables [O], synopsis
  • Computational Algebraic Topology [O], synopsis
  • Continuum Models in Industry [M], synopsis
  • Elasticity and Plasticity [M], synopsis
  • Finite Element Methods for PDEs [C], synopsis
  • Mathematical Analytics [O], synopsis
  • Mathematical Mechanical Biology [M], synopsis
  • Mathematical Models of Financial Derivatives [M], synopsis
  • Mathematics for Energy [M], synopsis
  • Networks [O], synopsis
  • Numerical Solution of Differential Equations II [C], synopsis
  • Stochastic Modelling of Biological Processes [M/C], synopsis
  • Waves and Compressible Flow [M], synopsis

Trinity Term 2018

  • C++ for Scientific Computing [C], synopsis
  • Python in Scientific Computing [C], synopsis
  • Randomised Algorithms for Matrix Computations and Data Analysis [C]