Saturday, December 20, 2014

[DMANET] PhD Studentships - Theoretical Analysis of Evolutionary Processes

PhD Studentships - Theoretical Analysis of Evolutionary Processes

Applications are invited for PhD studentships funded by the School of Computer Science, University of Nottingham. Studentships are available from October 2015 for a period of three years and include a stipend of £13,863 per year and tuition fees, and are available to students of any nationality. Applicants are expected to have a first-class Masters or Bachelors degree in Computer Science or related discipline, and must obtain support from a potential supervisor. I am happy support strong applicants interested in the following topic.

Evolutionary algorithms and other randomised search heuristics have been successfully applied to various industrial optimisation domains. However, the theoretical understanding of these methods has been limited. Recently, there has been significant progress in analysing the runtime (also called optimisation time) of randomised search heuristics using rigorous techniques from probability theory, randomised algorithms, and computational complexity. Results about the runtime give insights into how the behaviour of a randomised search heuristic depends on its parameter-settings and on the characteristics of the underlying optimisation problem.

The successful candidate(s) will contribute to this exciting research area, which lies at the interface between probability theory and theoretical computer science. The aim is to develop theory that aids in predicting and controlling the behaviour of evolutionary processes, both natural processes as well as in evolutionary algorithms.

The topic is mathematically challenging and requires an excellent degree in mathematics or computer science. In particular, the candidate should have a strong background in probability theory, discrete mathematics, and/or theoretical computer science.

The research will be carried out in the context of the EU-funded project Speed of Adaptation in Population Genetics and Evolutionary Computation (SAGE) which brings together researchers from population genetics and evolutionary computation. The studentship is locally associated with the Automated Scheduling, OptimisAtion and Planning (ASAP) research group, one of the five main Research Groups within the School of Computer Science at Nottingham.

For further information, please contact,

- Per Kristian Lehre <>

and see


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