Studentship: UKRI NetZero CDT PhD Studentship - and AI driven optimisation

Job Information

Area: Engineering

Location: UK Other

Closing Date: Wednesday 30 September 2026

Reference: ENG
407

Supervisors: Dr Ioanna Dimitriou, Dr Oliver Fisher

Programme Length: Four years

Contract Type: Full-time

Prospective

Start Date:

October 2026

The EPSRC and BBSRC Centre for Doctoral Training in Negative Emission Technologies for Net Zero (CDT in Net 2 Zero) is an equal partnership between Aston University (lead), University of Nottingham, Queen’s University Belfast, and University of Warwick. Through cutting‑edge research and interdisciplinary collaboration, this CDT tackles global challenges related to climate change and sustainability.

The four‑year doctoral programme trains the next generation of research leaders tasked with removing greenhouse gases from the environment. The CDT focuses on using biomass to replace fossil fuels and capture CO₂ from the atmosphere. The centre’s expertise covers Direct Air Capture and CO₂ Storage (DACCS), CO₂ utilisation, biochar synthesis and utilisation, biomass transition to materials and chemicals, and biomass to energy with carbon capture and storage (BECCS).

• Develop a network with doctoral researchers, academia, government, and industry.
• Access to cutting‑edge facilities and opportunities for international collaboration, preparing you for a successful career in academia, industry, or policy making.
• Carry out a training programme covering practical engineering, communication, entrepreneurship, and business skills to prepare students for diverse sectors.
• Have a three‑month placement with industry, research collaborators or policymakers.

As global energy demand rises, reducing carbon emissions is increasingly challenging. Gas‑turbine‑based power generation continues to play a central role in electricity supply, yet it is also a major source of CO₂ emissions and contributes to grid instability as renewable penetration increases. Achieving national net zero targets requires integrated solutions that decarbonise existing infrastructure, enhance grid flexibility, and enable sustainable energy carriers.

Hybrid energy systems offer a promising pathway, but current designs face important limitations. Many studies depend heavily on electricity‑intensive Power‑to‑X routes while under utilising thermochemical biomass conversion and advanced solar‑thermal technologies. Emerging carbon‑capture approaches such as electrochemically mediated amine regeneration show strong potential for flexible, low‑temperature operation, yet they remain largely unexplored within fully integrated hybrid systems. Current techno‑economic studies rely on steady‑state modelling and overlook dynamic behaviour under variable grid and weather conditions.

This PhD project aims to develop and evaluate a novel hybrid system that integrates gas turbines, low‑temperature carbon capture, biomass gasification, and advanced solar thermal applications to enable carbon‑negative fuel production and grid support. The research will involve thermodynamic modelling, transient simulation under UK climate and grid demand profiles, economic assessment, life‑cycle analysis, and AI‑driven multi‑objective optimisation. Though the initial focus is on gas turbines, the hybridisation framework will be transferable to other industrial and power‑generation applications, such as industrial furnaces and waste‑to‑energy plants.

The overarching objective is to design intelligent control strategies that coordinate energy flows, maximise CO₂ utilisation, and demonstrate the technical and economic viability of a closed‑loop carbon platform suitable for large‑scale deployment.

• Motivation, creativity, and resourcefulness.
• A mature approach to learning.
• Academic background: a Bachelors degree in Chemical Engineering, Mechanical Engineering, or a closely related discipline with an award of First Class or 2.1.
• Experience in, or willingness to learn, modelling and simulation tools such as MATLAB, Python, Engineering Equation Solver, Aspen Plus, and TRNSYS.
• A solid foundation in thermodynamics, process modelling, programming, or…