Aims

Modern scientific research often requires a computational approach, in conjunction with theoretical and experimental work. Graduates in mathematical...

Topics in Scientific Computing (NSCI0011)

Aims

Modern scientific research often requires a computational approach, in conjunction with theoretical and experimental work. Graduates in mathematical sciences are therefore expected to be conversant with the main “tools of the trade”, such as numerical methods and systems modelling, and should be able to identify opportunities to exploit these tools across a diverse range of practical scientific contexts.

In this module you will be introduced to computer-based numerical and algorithmic methods, with applications to problems. The module will cover contemporary techniques within different scientific contexts: finite difference and spectral methods, neural circuits and density functional theory. The module is delivered via a combination of workshops, exercises and project work.

Intended Learning Outcomes

Students should be able to:

Appreciate many of the benefits and limitations of computer packages for analysis, problem solving, and visualisation.
	Describe some of the contemporary trends in computer-based research within areas of mathematics, physics or biosciences, and recognise overlapping issues and common themes.
	Deploy accurately established computing techniques to analyse and solve problems across a range of contexts in physical or life sciences.
	Express arguments clearly and communicate complex information to non-specialist audiences.
	Demonstrate self-direction and originality in tackling and solving problems in complex and unpredictable situations, and exercise the independent learning ability, initiative and personal responsibility required for continuing development as a professional

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