SAILING Marie Sklodowska-Curie Doctoral Candidate (DC7)

FTE: 1.0

Term: Fixed for 36 months

Title: Doctoral Graduate Research Assistant (PhD studentship) in accurate spatial-temporal prediction of energy generation and demand

Start date: Between 1^st June 2026 and 1^st December 2026

The University of Exeter is recruiting a Graduate Research Assistant (PhD studentship) as part of the SAILING Doctoral Network, an EU-funded Marie Skłodowska Curie Actions (MSCA) programme (101227573). SAILING will train 12 next generation researchers to advance intelligent, automated and secure energy management systems for the Internet of Energy (IoE), working across digital twins, secure AI, energy optimisation, and fault detection. The network offers high quality training, international mobility, and collaboration across leading academic and industrial partners in Europe.

Exeter has 2 other vacancies: DC4 and DC11. See other advertisements.

This description is for the DC7 position only.

DC7: Accurate spatial-temporal prediction of energy generation and demand.

This specific Doctoral Graduate Researcher Assistant position DC7 on developing a hybrid prediction model to forecast variable energy generation and demand. The key objectives are to create

• A prediction model integrating the domain knowledge in IoE,
• A hybrid deep neural network for spatial-temporal information representation,
• And an effective feature selection mechanism for prediction.

The post will include 2 separate secondments, about 3-months duration each, to other EU and Associated Country partners of the SAILING Doctoral Network for training and collaboration purposes.

About you

You will be able to present research progress, communicate complex information clearly, and contribute to external funding proposals. Applicants must hold a first degree (or equivalent) in a relevant area, such as Computer Science, Communication Engineering, Electrical/Power Engineering, Energy Systems, Data Science, Applied Mathematics, Cybersecurity or Artificial Intelligence. Applicants will be able to:

• Demonstrate strong quantitative and analytical skills and an ability to learn new methods quickly. 
• Show interest in Computer Science/Internet-of-Energy/Cybersecurity/Artificial Intelligence and their data, modelling, and operational challenges.
• Develop and evaluate algorithmic solutions (e.g., machine learning, optimisation, statistical modelling, distributed systems), depending on project direction.
• Implement research prototypes and run reproducible experiments using programming and tooling.
• Work with datasets, including data preparation, experimental design, benchmarking, and reporting of results.
• Collaborate effectively with supervisors and partners, including contributing to network-wide training, secondments, and dissemination.

Please ensure you read the full Job Description and Person Specification for eligibility criteria.

What we can offer you

• A full employment contract for three years.
• Competitive MSCA-aligned salary plus allowances (values depend on exchange rate).
• Access to state-of-the-art facilities and expert supervision.
• International secondments, training events and collaboration with 11 fellow doctoral researchers.
• A supportive research environment on a beautiful Devon campus.

About the University of Exeter

The University of Exeter is an equal opportunity employer. We are officially recognised as a Disability Confident employer and an Athena Swan accredited institution. Whilst all applicants will be judged on merit alone, we particularly welcome applications from groups currently underrepresented in the workforce.

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