Last modified: 22 May 2019 17:07
This course was designed to show you what you can do with everything you learnt in your degree. We will use mathematical techniques to describe a fast variety of “real-world” systems: spreading of infectious diseases, onset of war, opinion formation, social systems, reliability of a space craft, patterns on the fur of animals (morphogenesis), formation of galaxies, traffic jams and others. This course will boost your employability and it will be exciting to see how everything you learnt comes together.
| Study Type | Undergraduate | Level | 4 |
|---|---|---|---|
| Term | Second Term | Credit Points | 15 credits (7.5 ECTS credits) |
| Campus | None. | Sustained Study | No |
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The course content reflects the learning outcomes and contains the material for the students to realize these. This course bridges the gap between standard courses in physical sciences, where successful mathematical models are described, and scientific research, where new mathematical models have to be developed. Students will learn the art of mathematical modelling, which will enable them to develop new mathematical models for the description of natural systems. Examples from a wide range of phenomena will be discussed, eg. from biology, ecology, engineering, physics, physiology and psychology. A focus will be the critical interpretation of the mathematical models and their predictions. The applicability of the models will be assessed and their use for the respective branch of the natural sciences will be discussed.
Information on contact teaching time is available from the course guide.
1st attempt: Continuous assessment (assignments & projects (80%); oral exam (20%)). 6 to 7 in course assessments (solutions to be presented on the board during tutorials), one presentation of the project, a four page manuscript using LaTeX in the style of PRL.
Formative assessment will be by means of a continuous dialogue with the lecturer and interaction with the same during the problem solving exercises and the developement of models.
Due to the nature of the (primarily) continuous assessment of the course - summative assessment will be on a continuous ongoing basis as project work is marked.
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