[Apologies for cross posting]
Research Fellow in Decision Support Systems School of Computing University of Leeds
Grade 7 £ 31,342 to £37,394 per annum
This is one of two posts being advertised concurrently to support two projects: the EPSRC funded "Assessing the Underworld project" (ATU) and the EU funded "New Technologies for Tunnelling and Underground Works (NeTTUN)" project.
The Assessing the Underworld (ATU) project focusses on detecting the condition of buried assets, and in particular to build a decision support system to assist those concerned with maintaining streets and the assets buried underneath them, based on sensor data, deterioration models, geological data, and other information. You will work collaboratively to build the decision support system, focussing on the higher level aspects, particularly those relating to databases, ontologies and reasoning.
Leeds is also involved in a workpackage of the NeTTUN project, developing a decision support system for tunnel maintenance, in collaboration with the French train company, SNCF. You will need to become familiar with this aspect of the project and to help in the final deliverable. Part of the work here will involve the use of machine learning techniques to infer priority orderings for maintenance of tunnel segment based on a database of historical inspection data.
Travel within the UK and the EU will be required to visit partners and for project meetings, and further afield as necessary for presentation of published papers in conferences. You will be expected to publish your research in conferences and journals and to write deliverables for the projects.
You will have a PhD (or be close to completion) in Computer Science or a related discipline along with relevant knowledge and experience of ontologies, data bases, web-based interfaces, and the construction of decision support systems.
This position is fixed term until 31 May 2017. The length of fixed term contract will depend upon the start date for this post.
Informal enquires to Professor Tony Cohn, tel+44 (0)11334 35482, email [log in to unmask]
For further details and to apply, see https://jobs.leeds.ac.uk/vacancy.aspx?ref=ENGCP1006