Bio-inspired meta-heuristics such as genetic algorithms, ant colony optimisation and artificial immune systems 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. Furthermore, given a class of bio-inspired algorithms it is unclear on which kind of problems it performs well and on which it performs poorly.
In recent years theoretical analyses have emerged that provide results about the performance of bio-inspired algorithms. They rigorously estimate the expected time required by the algorithms to find a satisfactory solution for various optimisation problems. Such analyses use mathematical techniques drawn and extended from the fields of randomised algorithms, probability theory and computational complexity. The results allow for insights into the working principles of bio- inspired meta-heuristics, enable the assessment of parameter choices and design aspects while contributing to the design of more powerful algorithms.
This studentship offers a valuable opportunity to work within this very active, challenging and exciting field of research at the intersection between computational complexity and bio-inspired computation. The successful applicant will also have the opportunity to further develop his/her research skills and expertise by collaborating with a wide range of top class researchers in bio- inspired computing who are partners of the EPSRC funded project. Project partners include, amongst others, research groups at the University of Birmingham, UK, at the Technical University of Denmark (DTU) in Lyngby, Denmark and at the University of Adelaide, Australia.
Applicants must have at least a 2.1 or above degree in Computer Science.
Outstanding applicants from Mathematics, Physics and Engineering will also be considered and are encouraged to apply.
The successful applicant must have excellent analytical and computational skills. They also must be an excellent team player who can work independently and communicate well with others. Since the project is theoretically challenging, strong mathematical and probability theory skills are required
If English is not your first language, you must have an IELTS score of 6.5 overall, with no less than 6.0 in each component.
How to apply:
To apply for the studentship, applicants need to apply directly to the University of Sheffield using the online application system. Please name Dr Pietro Oliveto as your proposed supervisor.
Complete an application for admission to the standard Computer Science PhD programme http://www.sheffield.ac.uk/postgraduate/research/apply
Applications should include a research proposal, CV, transcripts and two references.
The research proposal (up to 4 A4 pages, including references) should outline your reasons for applying for this studentship and how you would approach the researching, including details of your skills and experience.