PhD Studentship: Dynamic Performance and AI-Driven Optimisation of Hybrid Energy Systems for Net Zero

This fully funded PhD project aims to develop and evaluate a novel hybrid energy system integrating gas turbines, low-temperature carbon capture, biomass gasification, and advanced solar thermal technologies to enable carbon-negative fuel production and grid support.

The research will focus on developing intelligent energy systems capable of reducing carbon emissions, improving grid stability, and enhancing sustainable energy generation. The project combines thermodynamic modelling, transient simulation, techno-economic assessment, life cycle analysis, and AI-driven optimisation to support the UK's net-zero ambitions.

Research Objectives

The successful candidate will:
- Develop thermodynamic models of integrated hybrid energy systems.
- Conduct transient simulations using UK climate and grid demand profiles.
- Evaluate system performance under varying operating conditions.
- Perform techno-economic and life cycle assessments.
- Develop AI-driven optimisation and intelligent control strategies.
- Investigate opportunities for deployment across industrial applications, including steel, cement, and waste-to-energy sectors.

Supervisory Team

Dr Ioanna Dimitriou, University of Nottingham
Dr Oliver Fisher, University of Nottingham

About the Net2Zero Centre for Doctoral Training

The Net2Zero CDT is a partnership between Aston University, the University of Nottingham, Queen's University Belfast, and the University of Warwick. Students benefit from:
- Access to world-class research facilities.
- Collaboration with academic and industrial partners.
- International networking opportunities.
- Training in engineering, communication, entrepreneurship, and business skills.
- A three-month industrial, research, or policy placement.

Candidate Profile

Applicants should hold, or expect to obtain, a First-Class or strong 2:1 degree (or equivalent) in Chemical Engineering, Mechanical Engineering, Energy Engineering, Process Engineering, or a closely related discipline.

A background in thermodynamics, energy systems, process modelling, programming, or simulation tools such as MATLAB, Python, Aspen Plus, TRNSYS, or EES is desirable.

Funding Package

- UKRI tax-free stipend (£21,805 per annum for 2026/27)
- Full tuition fee support
- Research Training Support Grant (RTSG)

Eligibility

This opportunity is open to Home Fee Status candidates only.