School of Computer Science in the College of Engineering and Physical Sciences
University of Birmingham, Edgbaston, Birmingham, UK
Full time starting salary is normally in the range £31,406 to £40,927. With potential progression once in post to £43,434 a year.
Fixed-term for up to 3 years
Closing Date 31 October 2021
Applications are invited for a 3-year Research Fellowship in the theory of co-evolutionary computation. Co-evolutionary algorithms are heuristic optimisation techniques, mimicking biological principles of natural selection, e.g. for minimax/robust optimisation and learning game playing strategies. Such algorithms have been successfully applied to various industrial optimisation domains. However, the theoretical understanding of these methods has been limited.
The successful candidate will contribute, together with other project team members and international academic and industrial partners, towards developing the theoretical foundation necessary for the design of efficient and reliable co-evolutionary algorithms. The fellowship is funded by the UKRI Turing AI Acceleration Fellowship project “Rigorous Time-Complexity Analysis of co-Evolutionary Algorithms”, providing generous travel allowance, computing facilities etc.
Qualifications and Experience:
Hold (or be close to obtaining) a PhD in a relevant subject, ideally on the theory of evolutionary computation, algorithmic game theory, algorithms and computational complexity, stochastic processes/probability theory, or discrete mathematics.
Significant contributions made to world-class research in one or more of the above topics, experience in writing peer-reviewed papers for leading journals and conferences
Main Duties and Responsibilities:
Conduct original research according to agreed project aims.
Disseminate research findings through publications, seminars/presentations etc.
Assist in coordination and management of the above-mentioned project.
Work within specified research grants and projects and contribute to writing bids.
Skills and Knowledge:
High level analytical and computational skills.
Proficiency in (or desire to learn) mathematical techniques relevant for the analysis of evolutionary algorithms and other randomised algorithms.
Ability to communicate complex information clearly in written and spoken form.
Desirable/optional: (a) Programming skills, (b) Experience in collaborating with national and international academic and industrial partners.
Knowledge of the protected characteristics of the Equality Act 2010, and how to actively ensure in day to day activity in own area that those with protected characteristics are treated equally and fairly.
For further information please contact Dr Per Kristian Lehre, email@example.com
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