FUNDED PHD STUDENTSHIP FOR SEPTEMBER/OCTOBER 2007

 

Industrial CASE Studentship with BTExact: Design principles for Autonomic Systems.

Computer Science Supervisor: Prof. Mike Holcombe (m.holcombe@dcs.shef.ac.uk) from whom further details can be obtained.

 

Applications should be made as soon as possible through the University’s normal PhD application process.

 Further details.

 Design Principles for Autonomic systems – sponsored by BT

 

The goal of the project is to derive and develop Design Principles and Algorithms for “adaptive/intelligent infrastructure”. We already know that the nature of such solutions will be very different to typical systems today, and that our “toolbag” of techniques needs augmenting from other sources including inter-disciplinary solutions and unconventional – with respect to computer science – areas, such as biology and complexity science.

This project will draw on Sheffield’s existing strong inter-disciplinary programme which has linked Computer Science with Computational Biology and biological modelling, to re-apply and transfer ideas into the CS and “autonomic systems” domain.

The University of Sheffield has developed an extremely strong Computer Science department, still with healthy growth, and an excellent track record of interdisciplinary working. It also has good experience in nature-inspired systems research (e.g. resulting in papers in Nature journal), and has collaborated with (among others) computational biology departments, to bring in interdisciplinary thinking. 

 BT has a long-standing relationship with researchers and supervisors within the Dept. of Computer Science at the University of Sheffield and their interdisciplinary collaborators, including providing members of the Industrial Advisory Board, and providing industrial supervision of projects.

We are looking at methods for developing autonomous solutions to complex, decentralised and dynamic problems using our insights into how natural systems solve such problems. Recent modelling at Sheffield has developed a greater understanding of this, in real exemplar systems, than anywhere else. This is highly relevant for autonomic computing solutions. The usual EPSRC residency restrictions apply for this grant.