Lecturer in Energy and Artificial Intelligence(UK Sponsorship)
Job Description
Role Overview
University College London (UCL) is seeking to appoint a Lecturer in Energy and Artificial Intelligence within the UCL Energy Institute, part of the Bartlett School Environment, Energy and Resources (BEAMS).
This is an exciting academic opportunity for an emerging researcher whose work sits at the intersection of artificial intelligence, data science, and energy systems. The role focuses on applying advanced computational methods to address pressing global challenges such as climate change, energy transition, and sustainability.
You will contribute to both research excellence and teaching delivery, helping shape the next generation of professionals in energy systems, AI, and sustainability analytics.
Key Responsibilities
In this role, you will:
- Develop and lead an independent research programme in AI for energy systems
Apply machine learning and data science techniques to real-world energy and sustainability challenges
Work with large-scale and complex datasets, including energy consumption, infrastructure, and environmental data
Contribute to interdisciplinary research collaborations across academia, government, industry, and NGOs
Publish high-quality research in leading peer-reviewed journals
Support funding applications and research project development
Teach and supervise students across undergraduate and postgraduate programmes
Deliver modules in AI, machine learning, energy systems, and data analytics
About You
You are an ambitious and highly capable researcher with expertise in artificial intelligence applied to energy systems and sustainability.
You will bring:
- A PhD in AI, data science, energy systems, or a closely related discipline
Strong expertise in machine learning, deep learning, and statistical modelling
Experience working with large-scale datasets and computational modelling
Knowledge of techniques such as:
- Time-series forecasting
Reinforcement learning
Causal inference
Simulation and predictive modelling
Evidence of publishing in strong academic journals
Experience in university teaching or academic mentoring
Ability to develop an independent and impactful research agenda
You will also demonstrate the ability to translate advanced AI methods into practical solutions for energy transition and sustainability challenges.
Teaching & Academic Contribution
You will contribute to teaching across UCL’s energy and sustainability programmes, including:
- MSc Energy Systems and Data Analytics
BSc/MEng Sustainable Built Environments
Energy and Resources programmes
You will support curriculum development, student supervision, and innovative teaching in AI-driven energy modelling.
About UCL Energy Institute
The UCL Energy Institute is a globally recognised centre for research, education, and policy engagement in energy systems and climate solutions.
It focuses on:
- Energy transition and decarbonisation
Data-driven energy modelling
Sustainable urban systems
Climate and environmental policy support
The Institute works closely with international partners, policymakers, and industry leaders to support evidence-based decision-making in the global energy sector.
Research Environment
UCL BEAMS provides a multidisciplinary environment combining engineering, environment, and energy sciences. The department supports cutting-edge research aligned with global sustainability goals and the UK Net Zero strategy.
Equality, Diversity & Inclusion
UCL is committed to fostering an inclusive academic environment where diversity drives innovation and excellence. Applications are encouraged from underrepresented groups in STEM, including women, ethnic minority candidates, disabled individuals, and LGBTQ+ researchers.
Higher education equality framework
Visa & Employment Eligibility
This post is eligible for Skilled Worker visa sponsorship, subject to UKVI requirements.
- Official UK visa guidance
- General immigration and academic mobility
- All employment must comply with UK right-to-work regulations
Benefits
UCL offers a competitive and comprehensive benefits package, including:
- 41 days annual leave (including bank holidays and closure days)
Defined benefit pension scheme
Cycle-to-work and season ticket loan schemes
On-site nursery and gym facilities
Enhanced family leave policies
Employee wellbeing and support services
Application Process
- Closing date: 17 May 2026
Start date: 1 September 2026
Interviews and selection conducted following shortlisting
Applicants are encouraged to provide a detailed research and teaching statement aligned with AI and energy systems innovation.
Summary
This role offers the opportunity to join a world-leading institution at the forefront of artificial intelligence and energy research, contributing directly to global efforts on sustainability, climate action, and digital transformation of energy systems.
