Background: The UK and the World are rapidly shifting towards multi-energy systems, such as districts and industrial parks with large amounts of renewable electricity, renewable heating & cooling, clean fuels (e.g. H2,) as well as new energy technologies (e.g. heat pumps, energy storage, electrolysers, etc). However, how to best integrate renewable energy and new technologies is uncertain and poses significant challenges. It therefore remains unclear how future multi-energy systems will look like and how they will be operated reliably. The project focuses on creating the next generation multi-energy systems by understanding how to best integrate, optimize and manage renewable energy and energy technologies by leveraging AI, modelling techniques and optimization methods The successful candidate will develop, apply and validate AI-based models (based on machine learning, agent-based, mixed-integer programming, etc) primarily to: predict energy demand in multi-energy systems (electricity, heat) dynamically manage renewable energy technologies outputs and discovery & optimize new designs of future zero-carbon multi-energy systems. This PhD project will cooperate with national and international projects and you will contribute to develop real-life multi-energy energy systems by applying, training and validating models to systems in the UK and Europe. A prime example is our unique Birmingham Tyseley Energy Park. Requirements: Applicants should have a first-class degree or good 2:1 (or equivalent) in Energy Engineering, Mechanical Engineering, Electrical Engineering, Computer Science or a related field, ideally with prior experience in energy systems. The ideal applicant should possess relevant analytical skills, proficiency in programming, and proficiency in modelling in high-level programming environment (e.g. Python, Matlab, Julia, Modelica etc). Deadline: The position will be filled as soon as a suitable person has been found; hence you are encouraged to apply as soon as possible. PhD Starting October 2024 or soon after. Supervision Team & Further Info: Supervisors: Associate Prof. Adriano Sciacovelli and Associate Prof. Grant Wilson; School of Chemical Engineering and Birmingham Energy Institute For enquires and to apply please contact Adriano Sciacovelli at a.sciacovellibham.ac.uk and attach your CV Funding notes: A fully funded 3.5-year studentship inclusive of stipend and tuition fees for students eligible for Home fees. Overseas candidates will be considered for the position, nonetheless they should be able to cover the tuition fee difference. Supervisors remain available for online meeting to discuss further details. Offer also include access to state-of-the-art facilities and funding for travelling and engagement activities. A fully funded 3.5-year studentship