Lecturer / Associate Professor in Energy Innovation

UCL Energy Institute seeks an internationally recognized academic leader in applied energy research and innovation, who has led cross-disciplinary initiatives on large scale. They will have a distinguished research and teaching profile in quantitative methods, machine learning (ML) and Artificial Intelligence (AI) applications in the Energy field, and experience translating these cutting edge techniques in energy industry, government, or NGOs. They will have overseen high-quality, impactful research collaborations in energy and innovation, that address major societal challenges and opportunities associated with AI. They will guide the evolution of our energy and innovation research and programmes of activity, fostering strong external partnerships and pioneering international collaborations.

The role also carriers a significant contribution to the broader strategic development of energy, innovation and AI at the UCL Energy Institute, encompassing education, training, research, governance, and operational leadership. The successful candidate will further develop our teaching portfolio, including our MSc and BSc programmes, Energy Systems and Data Analytics and Sustainable Built Environments, Energy and Resources BSc and MEng.

This is a permanent role available from 1 September 2026.

About you

You have strong expertise in energy, innovation, AI/ML and advanced data analytics. You have deep experience applications across energy systems, urban environment, transport or the built environment. Your work involves large-scale energy datasets and big data analytics, and you have demonstrated expertise in translating advanced AI/ML methods into real-world applications. Innovative solutions in forecasting, simulation, optimisation, system thinking, causal modelling, technological interventions and policy evaluation would be particularly valuable. You have a strong track record of producing high-quality, impactful research demonstrated through publications in leading peer-reviewed journals and international collaborations. You have experience leading large-scale research projects, raising research funding and building partnerships across academia, industry, government or NGOs. Your work engages directly with stakeholders in the energy sector, contributing to the development of pr actical and scalable solutions for sustainable energy transitions. You are committed to excellence in teaching and student mentorship, with the ability to translate advanced AI and data analytics methods into engaging learning experiences. You have experience delivering taught modules related to energy, innovation, AI, and data-driven approaches to sustainability and energy systems.

You must hold a PhD in a relevant disciplined aligned with energy systems, innovation, AI, data science, or a closely related field with clear application to energy.

For appointment at Lecturer level, applicants should demonstrate a minimum of two years’ experience in research projects, publications, teaching experience, and student supervision.

For appointment at Associate Professor level, applicants must have at least five years’ experience, with proven track record of leading research projects, publications, delivering taught modules for MSc students and supervising PhD students with at least one to completion.

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.

Advert reference: B04-07321

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