PhD Studentship: AI‑Driven Sustainable Cooling Design

University of Birmingham; Birmingham; On-site; GBP 19,000 - 21,000; Full time

Benefits offered by this job

Funding

Job summary

The University of Birmingham invites applications for a PhD project to develop a physics-informed artificial intelligence framework for systematic design and optimisation of alternative cooling mechanisms and their refrigeration cycles. The project combines thermodynamic modelling, machine learning, and multi-objective optimisation.

You will join the School of Chemical Engineering at Birmingham, gaining hands-on experience in thermal energy experiments, simulation, and data analysis, with

Qualifications

• A good bachelor’s degree (first or upper second-class honours) or an MSc in Mechanical Engineering, Chemical Engineering, Materials Science, Physics, Energy or other relevant disciplines.
• Strong interest in thermal energy engineering with beneficial experience in combining computational and experimental work.
• Ability to work independently and in a research team, both autonomously and collaboratively.

Responsibilities

• Develop a physics-informed AI framework for systematic design and optimisation of cooling mechanisms and their refrigeration cycles.
• Integrate thermodynamic modelling, machine learning, and multi-objective optimisation to identify high-potential design options.
• Carry out experimental investigations to validate models and refine the computational framework.
• Balance experimental and computational work according to background and interests.

Skills

Thermal energy engineering

Computational & experimental work

Data analysis

Project management

Education

Bachelor’s degree or MSc in Mechanical/Chemical Eng/Materials/Physics/Energy

Job description

The University of Birmingham invites applications for a PhD project to develop a physics-informed artificial intelligence framework for systematic design and optimisation of alternative cooling mechanisms and their refrigeration cycles. The project combines thermodynamic modelling, machine learning, and multi-objective optimisation.

You will join the School of Chemical Engineering at Birmingham, gaining hands-on experience in thermal energy experiments, simulation, and data analysis, with