Which doctoral training programme is right for you?
The multidisciplinary science doctoral training programmes share a common focus on
the application of advanced methods from mathematics, statistics and engineering to problems in the natural sciences.
However, there are differences in emphasis. These are explained here to help you determine which programme will best suit your interests and abilities.
Focus on biomolecules
The Mathematical
Biology and Biophysical Chemistry MSc focuses on the biophysical chemistry of individual biomolecules and meso-scale aggregates of biomolecules,
without losing sight of the biological context (cell, tissue, organism).
The programme places a considerable emphasis on the interface with chemistry and physics,
as well as on data analysis and advanced instrumentation.
The miniprojects in the Master's year allow you to experience three different research cultures:
(i) life sciences; (ii) chemistry/physical chemistry; (iii) maths/stats/computational.
The MBBC MSc is followed by a three-year
Multidisciplinary Science PhD degree course.
Focus on integrative biology
The Systems
Biology MSc focuses on the interface between the life sciences and mathematics/statistics/bioinformatics.
The emphasis is on an integrative approach to biological problems;
important aspects of such an approach are analysis of high-throughput data,
connecting genes to function (gene regulatory networks, functional genomics/proteomics),
and linking levels of biological organisation (from molecule to whole-organism to community).
There are two miniprojects (one in the life sciences, one in maths/stats/bioinformatics).
The WSB MSc is followed by a
three-year PhD degree course
which integrates experimental and theoretical aspects of a biological research topic.
Focus on complex behaviour
The Complexity
Science MSc focuses on complex systems that consist of many interdependent components and exhibit self-organisation and emergent behaviour at the whole-system level.
The emphasis is on advanced computational techniques and their application to new fields where large amounts of quantitative data are becoming available, calling for innovative methods of analysis.
The techniques are drawn from mathematics (dynamical systems, chaos), statistics, physics (phase transitions), chemistry (self-assembly),
biology (network models, e.g. neuroscience, metabolism), and
computer science (agent-based modelling e.g. economics, finance).
Exciting new fields of application include transport, health and social communities.
There are two end-user oriented miniprojects; the Complexity MSc is followed by a
three-year PhD degree course.