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Lecturer in Data Analytics and Sustainability

UCL

Location: London, Hybrid
Salary: £54,931 to £64,644
Hours: Full Time
Contract Type: Permanent
Placed On: 15th December 2025
Closes: 14th January 2026
Job Ref: B04-06780

About us

We aim to support the development of a globally sustainable energy system by integrating multidisciplinary research—from data analytics to environmental economics—to analyse and model interactions across energy sectors, equip graduates for careers in industry, academia, and policy, and work with partners to ensure real-world impact. https://www.ucl.ac.uk/bartlett/energy/

About the role

We are recruiting a Lecturer in Energy Data Analytics and Sustainability, specialising in advanced data analytics, machine learning, and AI applications in the energy sector, with a strong interest in the energy transition, sustainability, and interdisciplinary collaboration.

The successful candidate will teaching in our programmes MSc and BSc programs, Sustainable Built Environments, Energy and Resources BSc and MEng and Energy Systems and Data Analytics through teaching of two core modules or equivalent, contributing to institutional roles and the leadership of MSc ESDA programme as Deputy Director. Contribute to teaching on other modules and programmes as appropriate. Supervision of students, including undergraduate and postgraduate level, being personal tutor for both undergraduate and postgraduate students. Develop research-led learning and teaching strategies in accordance with UCL’s Connected Curriculum. Set, mark and assess work and examinations and provide students with feedback. Develop a research portofolio and contribute to institutional roles.

This post is available from 1 July 2026.

UCL welcomes applications from international applicants and has licence to sponsor individuals who require a visa. This is dependent on the post and candidate meeting eligibility requirements for visa sponsorship under UK Visas and Immigration legislation.

About you

You will have strong expertise in advanced data analytics, machine learning, and AI applications in the energy sector, supported by a PhD in a quantitative discipline with a thesis directly relevant to the energy transition and the use of supervised, unsupervised, and advanced deep learning methods.

You will also bring substantial research experience in machine learning for energy, transport, or buildings including time-series forecasting, reinforcement learning for smart grid optimisation, causal inference for policy evaluation and experience in research-led teaching focused on data analytics and advanced ML methods.

What we offer

As well as the exciting opportunities this role presents, we also offer some great benefits, some of which are below:

  • 41 Days holiday (27 days annual leave, 8 bank holiday and 6 closure days)
  • Additional 5 days’ annual leave purchase scheme
  • Defined benefit career average revalued earnings pension scheme (CARE)
  • Cycle to work scheme and season ticket loan
  • Immigration loan
  • Relocation scheme for certain posts
  • On-site nursery
  • On-site gym
  • Enhanced maternity, paternity and adoption pay
  • Employee assistance programme: Staff Support Service
  • Discounted medical insurance

Visit https://www.ucl.ac.uk/work-at-ucl/rewards-and-benefits to find out more.

Our commitment to Equality, Diversity and Inclusion

As London’s Global University, we know diversity fosters creativity and innovation, and we want our community to represent the diversity of the world’s talent. We are committed to equality of opportunity, to being fair and inclusive, and to being a place where we all belong. We therefore particularly encourage applications from candidates who are likely to be underrepresented in UCL’s workforce. These include people from ethnic minority backgrounds; disabled people; LGBTQI+ people; and for our Grade 9 and 10 roles, women. Our department holds an Athena SWAN Silver award in recognition of our commitment and demonstrable impact in advancing gender equality.

Customer advert reference: B04-06780

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