Big Data Analytics: Visualising high-dimensional cost function landscapes - Computer Science - PhD (Funded)

Supervisors:
Professor Jonathan Fieldsend
Dr Ozgur Akman

Location: Streatham Campus, Exeter



The project will investigate and develop extensions to the local optima network framework for fitness landscape analysis of optimisation problems. Specifically, it will investigate methods for visualising continuous high-dimensional search, with real-world examples from the systems biology domain.

With the vast growth in scientific data, data visualisation methods have become ever more important. These are crucial to both bridge the gap between specialists and non-specialists (to aid the explanation of science and results), and also to investigate and probe the relationships within data (leading to new knowledge and discoveries).

One area where such visualisation is important is when visualising the properties of a problem that affect optimiser performance. For instance, visualisation of the fitness landscapes relating designs to their corresponding quality, and broader differences between design regions, is useful -- but difficult -- as the data may naturally live in a high number of dimensions. In the last decade, local optima networks (LONs) have arisen as a useful and compact representation of the fitness landscape in combinatorial spaces. However, their extension to continuous spaces is less well explored.

This College-funded PhD project, is closely aligned to the EPSRC-funded project, EP/N017846/1: The Parameter Optimisation Problem: Addressing a Key Challenge in Computational Systems Biology. It is concerned with the investigation and development of novel visualisation methods of the problem landscape associated with gene regulatory network models, with circadian clocks as a prototypical example. However, it is anticipated the work will be applicable to a broader range of problems.

The successful applicant will be embedded in a thriving research environment, which includes the recently opened Living Systems Institute: a £52.5 million investment into interdisciplinary approaches to understanding biological systems. The Computer Science and Mathematics departments at Exeter are dynamic and growing communities, with significant interactions, including a large and active body of postgraduate and postdoctoral researchers. The departments provide substantial support for postgraduate researchers, including the facility to attend appropriate masters level modules alongside their PhD projects. In addition, the applicant will have access to a broad range of centrally provided training courses relevant to this project (e.g. courses on utilising Exeter’s new £3 million high performance computing facility).
Entry requirements

Applicants for this studentship must have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK, in an appropriate area of science or technology.
If English is not your first language you will need to have achieved at least 6.5 in IELTS and no less than 6.0 in any section by the start of the project. Alternative tests may be acceptable (see http://www.exeter.ac.uk/postgraduate/apply/english/).