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  Developing UK energy portfolio strategy using Machine Learning modelling


   School of Computing

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  Dr Farzad Arabikhan  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

Applications are invited for a self-funded, 3-year full-time or 6-year part time PhD project.

The PhD will be based in the School of Computing and will be supervised by Dr Farzad Arabikhan and Professor Dylan Jones.

The work on this project could involve:

  • Analysing sustainable energy resources and their contribution to the UK energy portfolio
  • Utilising optimisation methods and applying operational research techniques.
  • Data modelling using data science techniques from the fields of Machine Learning and Artificial Intelligence

Project description

There are different sources of energy such as fossil, nuclear, renewable, etc. but global and governmental obligations are pushing towards reducing carbon emission and transitioning to the use of renewable resources. Sustainable, affordable and clean energy supply is now a critical mission and duty of the UK government to support the households and businesses. Also, there are rich sources of datasets regarding the energy demand, supply and consumptions which can be utilised to optimise the energy supply portfolio using novel techniques from the field of Machine Learning (ML) and Artificial Intelligence (AI).  

The aim of this proposed research is to develop multiple criteria models that recommend energy portfolios using ML and AI to:

  • Achieve renewable energy national and global targets
  • Minimise risk of electricity shortage across UK
  • Minimise total costs
  • Maximise social acceptability

The supervision team has extensive knowledge in renewable energy, optimisation and operational research , and machine learning and artificial intelligence fields and has been involved in many research and knowledge transfer projects. The team members are also very much experienced in supervising PhD projects and have had many successful PhD completions. Furthermore, the University of Portsmouth has exceptional facilities which supports well the PhD candidates to undertake original research and to be recognised nationally and internationally as independent researchers. The successful PhD candidate who completes this project will have great chances to continue their career as a researcher in research and academic institutes and also to work in industry as an expert in the energy and data science fields.

General admissions criteria

You'll need a good first degree from an internationally recognised university or a Master’s degree in an appropriate subject. In exceptional cases, we may consider equivalent professional experience and/or qualifications. English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.

Specific candidate requirements

The candidate should have minimum knowledge of computer programming using R or Python

How to Apply

We encourage you to contact Dr Farzad Arabikhan ([Email Address Removed]) to discuss your interest before you apply, quoting the project code below.

When you are ready to apply, please follow the 'Apply now' link on the Computing PhD subject area page and select the link for the relevant intake. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV. Our ‘How to Apply’ page offers further guidance on the PhD application process. 

When applying please quote project code:COMP7600423


Computer Science (8) Engineering (12) Mathematics (25)

Funding Notes

Self-funded PhD students only.
PhD full-time and part-time courses are eligible for the UK Government Doctoral Loan (UK students only).