About the Project
Applications are invited for a PhD studentship to start October 2016. This studentship is one of two projects in this area of research and will be based in the School of Business and Economics working alongside the Wolfson School of Engineering.
We are moving into a new era of smart cities with increasingly interconnected infrastructure systems comprising transport systems, utilities (water, gas and electricity), low impact development, bridges, telecommunications, etc., to provide commodities and services essential to enable, sustain, or enhance societal living conditions. However, the notion of interconnected systems of systems is presenting new challenges for urban planners that will require a paradigm shift in thinking and ultimately how future infrastructure is managed and supported. Coupled with this transformation is the exponential growth in data from sensors, measurement systems, databases and complex data-driven simulations. However, data alone is insufficient - what is really required is intelligently processing of the data with new knowledge/information management techniques to gain understanding of the complex interactions. The goal is to create a unique knowledge base built upon greater understanding of the complex interactions/emergent behaviour (undesirable and desirable) that will be inherent in all infrastructure systems of systems. Whilst data science goes some way towards the development of data processing algorithms, it does not provide crucial understanding at a system of systems engineering level of the complex interactions.
This exciting research will contribute towards the recently announced £138m investment in UK Collaboratorium for Research in Infrastructure & Cities (ukcric.co.uk). The PhD students will work across the intersection between systems modelling and knowledge/ information management to create an exploratory knowledge elicitation platform where the complex interactions between infrastructure SoS can be investigated such as risk and resilience strategies, failure mode interventions and adaptable/sustainable infrastructure architectures at the SoS level.
This studentship will focus on big data analytics involving modelling, simulation and visualization of system of systems infrastructure architectures to understand and predict complex infrastructure interactions at a systems of systems level.
This project is funded partly by the Engineering and Physical Sciences Research Council (EPSRC) as part of the Doctoral Training Partnership (DTP) awarded to Loughborough University, and partly by the School of Business and Economics.
Benefits of this DTP-studentship include:
• A tax-free stipend of £14,296 per annum for 3.5 years. The stipend will increase in line with EPSRC recommended rates.
• Tuition fees at the UK/EU rate, for up to 3.5 years.
• A Research Training Support Grant worth at least £1,750 to assist with training over the course of the studentship.
• Admission to the University as part of a cohort of EPSRC-DTP funded PhD students
Due to funding restrictions, this is only available to those who are eligible to pay UK/EU fees. In order to qualify for a full award, all applicants must meet the EPSRC eligibility criteria including the minimum residency requirement https://www.epsrc.ac.uk/skills/students/help/eligibility/
Students will normally need to hold, or expect to gain, an honours degree equivalent of a UK 2:1 minimum, with a preference for masters’ degree (with average programme mark of no less than 65%) or first-class honours equivalent in knowledge/information management.
General information about the studentship in the School of Business and Economics - Centre for Information Management can be found at: http://www.lboro.ac.uk/research/cim/ or from Professor Tom Jackson ([Email Address Removed], tel +44 (0)1509 635666)
To apply, please complete the online application using the following link: http://www.lboro.ac.uk/study/apply/research/. Under programme name, please select ‘Centre for Information Management’.
Deadline: 25 May 2016
Please quote reference: GSRC2016CEI/TJ
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