EDF has an R&D centre in the UK with around 50 researchers in situ. The centre is an integral part of the EDF Group R&D network and works across the whole value chain of electricity; successfully leading on millions of pounds worth of international projects. Find out more.

EDF Research and Development (R&D UK) works in partnership with a number of universities across the UK. They offer research opportunities, giving students the chance to develop their academic qualifications; Doctor of Philosophy (PhD) and Engineering Doctorate (EngD), whilst gaining industrial experience within one of the onsite teams. 

Why join us?

• Chance to innovate on behalf of our customers, developing sophisticated, real-world tools and processes,

• Help to build new partnerships, strengthening our position in Europe and developing robust low-carbon energy solutions.

What we're looking for

You will have:

  • A bachelor’s degree with a minimum of upper second-class (2:1) honours, or an overseas qualification of an equivalent standard.
  • A Masters degree in statistics, engineering, computer science or other relevant disciplines. Candidates without a Masters degree may be admitted where suitable experience is demonstrated.
  • Expert knowledge of machine learning and artificial intelligence methods.
  • An understanding of the energy system and the role of suppliers
  • Excellent numerical and computing skills.
  • Excellent interpersonal and communication skills (oral and written).

Where could it take you?

Claire Canning’s experience: Clare joined the R&D UK Renewables team on a placement within her Engineering Doctorate.

Read here about how her time within R&D UK helped her to build her confidence. 

About this PhD

Artificial Intelligence promises to be one of the most transformative technologies of the modern century. Recent progress and breakthroughs in deep learning have enabled a host of new applications across a range of fields from protein folding to autonomous vehicles. However, in the energy system the adoption of these methods has been limited by their ‘black-box’ nature.

Critical infrastructure, like energy systems, operate under stringent reliability and resilience requirements. Greater adoption of AI in this sector demands methods that can provide insights into how an algorithm is making decisions and predictions. This will give operators of these systems confidence in the reliability of these algorithms.

This PhD will explore and develop Explainable AI (XAI) for energy systems. These methods will be able to provide insights into how the ‘black-box’ methods are functioning, approaching glass-box methods. The research contribution will cover a wide spectrum building theoretical foundations in this rapidly developing field while also contributing to real world applications such as wind turbine failure. The research will be conducted as a collaboration between the EDF Digital Innovation team and the UCL Energy Institute (UCL EI) at the Bartlett School of Energy, Environment and Resources (BSEER).

The deadline for applications is: 09.00 am, Tuesday 8 June 2021

Interviews will be held online during the week of 28th June 2021


Your location will usually be at the University offering the PhD, with some time spent in our offices.

Rewards and benefits

As the students taking up these research positions will be employed by a university, the pay rates and benefits will depend on that offered by the university, and also will change from opportunity to opportunity. Interested students would need to check each individual opportunity to receive further details on the remuneration.


We're not currently recruiting for any Postgraduate opportunities. Please do check back in Autumn 2021 for further updates.