The Institute of Industrial Research (IIR)/Centre of Intelligent Data Solutions (CIDS) research spans across computer science, engineering systems, and mathematics, it recognised by league tables and through national research assessment exercises. Our research ranges from the basic to the applied, and takes place over the full range of physical scales. Collaborations with industry and the use of national and international facilities are frequent. Our research’s fiscal activity is from public and industrial sources, during 2013/2014 was over £3.2M. As part of our strategy, our aim is to strengthen our research team currently working on condition based monitoring systems to enhance the academic side of the work, offering practical solutions to industrial and marine problems.  This post will involve close working with academic researchers and industrial engineers in teams who will be developing and applying concepts of statistical prediction, to be used in future prototype products and services.  Currently our project portfolio includes many InnovateUK funded research and development collaborations, all of which will feature with software embedded in an autonomous condition monitoring system.

Handling large volumes of data using artificial intelligence techniques to extract important features and classification algorithms to evaluate engine condition automatically with very little human interaction. Once completed this autonomous system will operate with extensive use of prediction techniques rather than employing a large numbers of sensors.  The successful candidate must be educated to degree level in the area of electrical/mechanical engineering, applied physics, computer science or applied mathematics. A PhD would be preferred which incorporated the practical use of AI in one of these areas.

The candidate will have a combination of the following proficiencies to demonstrate their suitability for the role.

·         Practical experience of the use of Artificial Intelligence and statistical prediction techniques

·         Real–time data handling skills using techniques to retrieve and cluster raw data

·         A track record of research journal publications

·         Skilled with developing concepts using Matlab or any high level language

·         A functional understanding of electro-mechanical systems

21 June 2015

Interview date: 6 July 2015