PhD Research Studentships

Quantum Computing and AI for Nonlinear Dynamics

Supervisor: Amin PAYKANI
Apply by:27 January 2027
Start in:September (Semester 1)

Description

Project Summary: A PhD opportunity is available at Queen Mary University of London to

develop advanced computational methods for simulating nonlinear dynamical systems using

physics-informed artificial intelligence (AI) and hybrid quantum-classical algorithms. The

project brings together expertise in scientific machine learning, computational modelling and

quantum computing, with a particular focus on stiff chemical reaction systems relevant to

sustainable fuels, including hydrogen and ammonia.

Nonlinear dynamical systems are central to numerous scientific and engineering applications,

from chemical reaction kinetics and combustion to energy conversion and complex physical

processes. Their governing equations often involve strongly coupled, nonlinear and stiff

differential equations, making accurate numerical simulation computationally demanding. In

detailed chemical kinetics, for example, conventional numerical solvers can become a major

bottleneck in high-fidelity combustion simulations. Recent advances in scientific AI offer

opportunities to accelerate these calculations, but maintaining physical consistency, numerical

stability and predictive reliability remains challenging. Emerging quantum algorithms and

hybrid quantum-classical computing provide alternative approaches to selected computational

operations underlying the simulation of dynamical systems. However, their applicability,

efficiency and potential advantages for nonlinear and stiff systems remain largely unexplored.

This PhD will investigate computational strategies that integrate physics-informed AI,

structure-preserving numerical methods and hybrid quantum-classical algorithms. The

research will examine how physical constraints, numerical approximations and quantum

computing techniques can be combined to improve computational efficiency while preserving

accuracy and stability. Chemical reaction kinetics will serve as a primary application and

benchmarking platform, with an emphasis on hydrogen and ammonia reaction mechanisms.

The project will combine numerical analysis, scientific computing, machine learning and

quantum algorithm development. Established classical methods will provide rigorous

benchmarks, while the quantum computing component will investigate the feasibility,

computational requirements and limitations of emerging approaches without assuming

quantum advantage.

The successful candidate will benefit from interdisciplinary supervision, computational

research facilities and training in scientific machine learning, numerical methods, chemical

kinetics and quantum algorithms. The research aims to establish new computational

methodologies with potential applications across sustainable energy technologies and broader

scientific and engineering systems governed by nonlinear dynamics.

Apply to QMUL for the scholarship https://www.qmul.ac.uk/postgraduate/research/applying-for-a-research-degree/ and select Sep entry for mechanical engineering) by the deadline of Wednesday 27th January 2027 16:00 GMT. 

Funding

Funded by: China Scholarship Council
Candidate will need to secure a CSC scholarship.
Under the scheme, Queen Mary will provide scholarships to cover all tuition fees, whilst the CSC will provide living expenses and one return flight ticket to successful applicants.
Only Chinese applicants can apply for this funding. The apply button may not be operational and so please apply here: www.qmul.ac.uk/postgraduate/research/applying-for-a-resea... and select Sep entry for mechanical engineering

Eligibility

  • Please be aware this site is being migrated to a new web system, and if you are unable to apply at the links we will add the links to the new PhD programmes. In the meantime if you would like to contact the Admissions Office directly you can do so via https://www.qmul.ac.uk/postgraduate/research/applying-for-a-research-degree/
  • The minimum requirement for this studentship opportunity is a good honours degree (minimum 2(i) honours or equivalent) or MSc/MRes in a relevant discipline.
  • If English is not your first language, you will require a valid English certificate equivalent to IELTS 6.5+ overall with a minimum score of minimum score of 6.0 in each of Writing, Listening, Reading and Speaking).
  • Note for EPSRC studentships; these studentships are open to those with Home fee status; according to the EPSRC terms and conditions.
  • Candidates are expected to start in September (Semester 1).

Contact

For informal enquiries about this opportunity, please contact Amin PAYKANI.

Apply

Start an application for this studentship and for entry onto the PhD FT Mechanical Engineering full-time programme (Semester 1 / September start):

Apply Now »

Please be sure to quote the reference "SEMS-PHD-738" to associate your application with this studentship opportunity.

Keywords:Artificial Intelligence, Automotive Engineering, Fluid Mechanics, Mechanics, Thermodynamics, Computational Physics