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- Tasks: Teach and research AI applications in energy systems, developing innovative solutions.
- Company: Join UCL Energy Institute, a leader in energy and AI research.
- Benefits: Competitive salary, hybrid work options, and opportunities for professional growth.
- Other info: Permanent position with excellent career development in a dynamic environment.
- Why this job: Make a real impact on sustainable energy through cutting-edge AI research.
- Qualifications: PhD in AI or related field, with teaching and research experience.
The predicted salary is between 54931 - 64644 £ per year.
The UCL Energy Institute (EI) is recruiting a Lecturer in Energy and Artificial Intelligence. This role is suited for an emerging researcher with strong research in AI and energy, and experience in teaching. The successful candidate will contribute to the Institute’s research and teaching activities, including the development and application of advanced machine-learning models and big data analytics in energy systems.
You will support research collaborations that advance the field, contribute to applied energy solutions, and engage with stakeholders across academia, industry, government, and NGOs. You will also play an active role in the delivery of UCL’s teaching programmes, helping develop students’ skills in AI, data analytics, and sustainable energy systems.
The successful candidate will develop an independent research agenda in AI for energy, contribute to teaching across MSc and BSc programmes Energy Systems and Data Analytics and Sustainable Built Environments, Energy and Resources BSc and MEng by teaching two modules. This post is permanent and available from 1 September 2026.
You are an internationally recognised researcher with strong expertise in artificial intelligence, machine learning, and data analytics applied to energy systems and sustainability challenges. You have experience in supervised and unsupervised learning methods, and in deploying deep learning architectures across energy systems, urban environment or transport.
Your work involves large-scale energy data sets and big data analytics, and you have demonstrated expertise applying AI/ML techniques to real-world energy problems. Experience in time-series modelling, simulation forecasting, reinforcement learning, and causal modelling approaches for evaluating the impacts of policy and technological interventions would be particularly valuable.
You have a track record of producing research outputs in peer-reviewed journals and can demonstrate potential to develop an independent research programme. You are committed to teaching and student mentorship, with experience in delivering taught modules in AI, ML and data-driven approaches to energy systems, sustainability, and innovation.
You hold a PhD in a relevant field, such as artificial intelligence, data science, or energy systems, with a clear focus on applications in the energy sector. You have experience in research and teaching, and have contributed to applied energy research projects or collaborations that demonstrate the practical impact of AI and machine learning methods in energy systems.
Lecturer in Energy and Artificial Intelligence employer: UK Energy Research Centre (UKERC)
Contact Detail:
UK Energy Research Centre (UKERC) Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lecturer in Energy and Artificial Intelligence
✨Tip Number 1
Network like a pro! Reach out to folks in your field, attend relevant events, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your expertise! Prepare a portfolio or presentation that highlights your research and teaching experience in AI and energy systems. This will help you stand out during interviews and showcase your skills effectively.
✨Tip Number 3
Practice makes perfect! Conduct mock interviews with friends or mentors to refine your responses and boost your confidence. Focus on articulating how your background aligns with the role and the impact you can make at UCL.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you’re genuinely interested in joining our team and contributing to the exciting work we do in energy and AI.
We think you need these skills to ace Lecturer in Energy and Artificial Intelligence
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in AI and energy systems. We want to see how your skills align with the role, so don’t be shy about showcasing your research and teaching experience!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about the intersection of energy and AI. We love seeing candidates who can articulate their vision for contributing to our research and teaching activities.
Showcase Your Research Impact: When detailing your research outputs, focus on the real-world impact of your work. We’re looking for evidence of how your AI/ML techniques have made a difference in energy systems, so share those success stories!
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. We can’t wait to hear from you!
How to prepare for a job interview at UK Energy Research Centre (UKERC)
✨Know Your Stuff
Make sure you brush up on the latest trends in AI and energy systems. Be ready to discuss your research and how it applies to real-world energy problems. Familiarise yourself with the specific machine-learning models and big data analytics techniques that are relevant to the role.
✨Showcase Your Teaching Experience
Prepare to talk about your teaching philosophy and any modules you've delivered in AI, ML, or energy systems. Think of examples where you've successfully engaged students or adapted your teaching methods to meet diverse learning needs.
✨Engage with Real-World Applications
Be ready to discuss how your research can contribute to applied energy solutions. Highlight any collaborations you've had with industry, government, or NGOs, and how these experiences have shaped your approach to research and teaching.
✨Ask Thoughtful Questions
Prepare some insightful questions about the UCL Energy Institute's current projects or future directions. This shows your genuine interest in the role and helps you assess if it's the right fit for you.