New PhD studentship in AI Methods for Energy Demand Data
28 September 2020
The UCL Energy Institute invites applications for a fully-funded four-year PhD studentship.
- Primary supervisor: Dr Aidan O’Sullivan
- Secondary supervisor: Prof Tadj Oreszczyn
- Scholarship covers: 4 years tuition fees (UK/EU rate); 4 years stipend (£17,285 for 2020/21)
- Start Date: Autumn term 2020
- Funded by: EPSRC and EDF (CASE)
- Eligibility: In addition to UCL's academic requirements for admittance to Doctoral studies, candidates should meet the EPSRC requirements.
About the studentship
The Energy Sector is undergoing a digital transformation that is producing data at a scale and resolution never before seen by the industry. Making best use of this data is vital to decarbonising the sector. The nationwide deployment of smart meters, which record high resolution electricity consumption data, will produce a vast amount of data on customer energy demand. In order to handle the scale and complexity of this data Artificial Intelligence methods are required that can intelligently extract patterns and insights on the behaviour driving energy consumption. Enhancing our understanding of the factors driving patterns of behaviour will yield a new demographics of energy consumption.
This PhD, in collaboration with EDF, will explore and develop novel Artificial Intelligence algorithms that extract valuable insights from smart meter data. Methods explored will include but are not limited to; reinforcement learning, unsupervised learning and causal inference. Geospatial analysis and data visualization will also be key. The research contribution will cover a wide spectrum building theoretical foundations in this rapidly developing field while also providing real world use cases. The research will require working with large and heterogeneous sources of data from; demographics, weather, geospatial.
Candidates should 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).
Applicants should access the UCL SELECT portal.
Scroll to the bottom of the page and click the ‘Apply now’ button.
- A covering letter.
- Names and addresses of two academic referees.
- Copies of your degree certificate(s) and transcript(s).
- A short research proposal (1000 words).
For informal enquiries on the research topic or your eligibility, email Dr Aidan O’Sullivan with ‘AI Methods for Energy Demand Data’ in the subject field.
Deadline for applications: Tuesday 7 December 2020, 9am (BST).
Interviews will be held online during the week of 14 December 2020.