Research Associate, Faculty of Engineering, Environment and Computing
We invite applications from researchers to join an EPSRC project which will use machine learning techniques to improve sophisticated symbolic computation algorithms within computer algebra systems.
Symbolic Computation produces exact answers to mathematical problems, automating and extending the pen and paper mathematics learnt at school. Implemented in Computer Algebra Systems; such algorithms prize correctness. The project will apply the inherently probabilistic techniques of machine learning to improve such algorithms by assisting with a variety of choices which choices which, while not affecting the correctness of the final answer, can have a substantial effect on the resources required to find it. This project will determine which machine learning techniques are suitable for adaption here and thus produce world-leading procedures, in particular, those to solve the problem of quantifier elimination in real closed fields.
The Research Associate will work within the Faculty of Engineering, Environment and Computing at Coventry University, and in particular with project leader Dr Matthew England who has extensive experience with symbolic computation.
Candidates are expected to already have expertise and experience in applying, optimizing and evaluating machine learning techniques. In particular, they should already possess a PhD in data sciences or machine learning and have a strong background in both mathematics and computer science. Excellent written and oral communication skills and advanced programming proficiency are essential.
The main duties of the successful candidate will be to generate suitable test data sets and run the machine learning experiments. Additional duties will include liaising with project partners both in the UK and abroad, contributing to and journal papers, and presenting results to various stakeholders.
For informal discussions contact: Matthew.England@coventry.ac.uk