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Data Analytics for Intelligent Integrated Energy Systems (WS15)

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  • Full or part time
    Dr P Rowley
    Dr E Barbour
  • Application Deadline
    No more applications being accepted
  • Competition Funded PhD Project (Students Worldwide)
    Competition Funded PhD Project (Students Worldwide)

Project Description

Loughborough University is a top-ten rated university in England for research intensity (REF2014). In choosing Loughborough for your research, you’ll work alongside academics who are leaders in their field. You will benefit from comprehensive support and guidance from our Doctoral College, including tailored careers advice, to help you succeed in your research and future career.
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Full Project Detail

In order to address the climate emergency, we must reduce our dependency on fossil fuels by stimulating energy savings and the use of renewable energy. Integrating large shares of intermittent energy sources such as solar and wind energy into our current system in a reliable way presents real engineering, financial and societal challenges. In parallel, the shift towards electricity use for transport and space heating and cooling adds to these challenges.
A new ‘intelligent’ approach to energy supply, storage and consumption is therefore needed that optimally matches supply and demand – including the development of data-driven methods of managing the integrated energy systems of the future.
Building on our current portfolio of research at CREST (Loughborough’s Centre for Renewable Energy Systems Technology), you will work with global experts on the development of a data-driven multi-parametric environment that facilitates multi-scale analysis of different future energy transition pathways. In order to manage the varying degrees of uncertainty inherent in the scenarios, the work will involve the development of statistical/probabilistic modelling approaches, such as those based on Bayesian methods.

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Entry requirements

Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) in mathematics, physics, engineering, computer science, or a related subject. A relevant Master’s degree and/or experience in one or more of the following will be an advantage: data analytics, statistics, artificial intelligence; machine learning or related subjects.

Funding Notes

Please note that studentships will be awarded on a competitive basis to applicants who have applied to this project and other advertised projects starting with advert reference ‘WS’ for the School of Mechanical, Electrical and Manufacturing Engineering.
If awarded, each 3-year studentship will provide a tax-free stipend of £15,009 p/a, plus tuition fees at the UK/EU rate (currently £4,327 p/a). While we welcome applications from non-EU nationals, please be advised that it will only be possible to fund the tuition fees at the international rate and no stipend will be available. Successful candidates will be notified by 30th September 2019.

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