offering a fully funded 3 year PhD scholarship on Theory of Bio-inspired
Algorithms.
Bio-inspired algorithms include general-purpose optimisers like
evolutionary algorithms, ant colony optimisation and particle swarm
optimisation. They mimic powerful mechanisms from nature, such as the
natural evolution of species or the collective intelligence of a swarm
of animals, and apply these mechanisms for solving complex optimisation
problems. Bio-inspired algorithms have been applied to a broad range of
problems in various disciplines with remarkable success. However, the
reasons behind their success are often elusive: their performance often
depends crucially, and unpredictably, on design choices and parameters.
This lack of understanding represents a major obstacle for the uptake
and usage of bio-inspired algorithms and for developing more effective
variants thereof.
This studentship is based in the area of runtime analysis, which can
provide such an understanding and has emerged as one of the major
theories in the field. Runtime analysis rigorously estimates the
expected time until an algorithm finds satisfactory solutions for
illustrative and relevant optimisation problems; a vital stepping stone
towards designing more efficient bio-inspired algorithms. Analyses use
algorithmic and mathematical techniques from the analysis of randomised
algorithms, probability theory and computational complexity. The results
allow for insights into the working principles of bio-inspired
algorithms, enable the assessment of parameter choices and design
aspects, and contribute to the design of more powerful algorithms.
The candidate will be working with Dr. Dirk Sudholt (supervisor) and Dr.
Pietro Oliveto at the University of Sheffield, and benefit from a wide
network of collaborators in the UK and around the world. In addition,
candidates may contribute to the SAGE project (Speed of Adaptation in
Population Genetics and Evolutionary Computation,
http://www.project-sage.eu), an ambitious interdisciplinary project
funded by the EU's Future and Emerging Technologies scheme. SAGE aims at
bringing together Population Genetics and Evolutionary Computation to
develop a unified theory describing the speed of adaptation in both
biological and artificial evolution.
Funding Notes:
The award covers UK fees and a stipend at the standard UK research rate
of £13,726 per annum.
Applicants should have, or expect to achieve, a minimum of an
upper-second-class Honours degree (2.1 or above) or a Master´s degree in
Computer Science, Mathematics, or related disciplines (or equivalent).
The project is mathematically challenging. Expertise with algorithmic
analysis, probability theory or bio-inspired algorithms is desirable.
Curiosity, excellent analytical thinking and an interest in these areas
are essential.
UK applicants and EU applicants are eligible for a full scholarship
award. International non-EU applicants cannot be funded and are not
eligible to apply.
To apply, please use the University's online application form at
http://www.shef.ac.uk/postgraduate/online and name Dr. Dirk Sudholt
asked to name a supervisor.
Application closing date is 15 March 2014. The position will remain open
until filled.
For informal enquiries please contact Dr. Dirk Sudholt at
d.sudholt@sheffield.ac.uk.
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