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School of Biological and Behavioural Sciences

Bypassing expensive calculations: Predicting the properties of photosynthetic proteins with an AI assistant

Research environment

The School of Biological and Behavioural Sciences (SBBS) at Queen Mary is one of the UK’s elite research centres, according to the 2014 Research Excellence Framework (REF). We offer a multi-disciplinary research environment and have approximately 150 PhD students working on projects in the biological and psychological sciences. Our students have access to a variety of research facilities supported by experienced staff, as well as a range of student support services.

Dr C Duffy is a theoretical biophysicist and his group is part of the photosynthesis and bioenergetics community in the School of Biological and Behavioural Sciences. His group recently joined (and is now located at) the Digital Environment Research Institue (DERI) in Whitechapel. This is a cuting edge and multi-disciplinary research institute focussing on applications of data, machine learning and computational techniques in science, medicine and the humanities.

Dr L Rossi is a Lecturer in AI in the School of Electronic Engineering and Computer Science and a member of DERI. His research covers Structural Pattern Recognition, Machine Learning, Data and Network Science.

Training and development

Our PhD students become part of Queen Mary’s Doctoral College which provides training and development opportunities, advice on funding, and financial support for research. Our students also have access to a Researcher Development Programme designed to help recognise and develop key skills and attributes needed to effectively manage research, and to prepare and plan for the next stages of their career.

This is a computational/theoretical project. The student will be given expert training in the quantum mechanics of open systems, quantum chemical techniques and molecular simulations, machine learning, and the theory of optics and light-harvesting. In addition the student will be encouraged to write papers and present finding at local and internation conferences.

Project description

Photosynthetic proteins are light-harvesting structures of extreme interest to research into biomimetic/hybrid solar technology, crop optimization and quantum biology. Understanding them requires ultra-fast, non-linear spectroscopy, interpreted through detailed simulation of energy transfer and relaxation. The current pipeline is:

  1. Molecular Dynamics (MD) simulation of the protein.
  2. For a set (>1000) of snapshots the excitation energy (ΔE) and the transition density (ρtd) of each chromophore is calculated using Quantum Chemistry (QC).
  3. ΔE and ρtd are used to calculate inter-chromophore interactions and define the exciton Hamiltonian.
  4. The Liouville-von Neumann (LvN) equation is (approximately) solved to yield the quantum/spectral dynamics.

This is an expensive, repetitive and not-very-scalable process and seems like an ideal problem for an AI. However, we still want to explain the relationship between structure and function. We therefore propose to use a hybrid approach in which Graph Neural Networks (GNNs) are trained to approximate the expensive parts of this pipeline while retaining physical detail and explainability.


This studentship is open to students applying for China Scholarship Council funding. Queen Mary University of London has partnered with the China Scholarship Council (CSC) to offer a joint scholarship programme to enable Chinese students to study for a PhD programme at Queen Mary. Under the scheme, Queen Mary will provide scholarships to cover all tuition fees, whilst the CSC will provide living expenses for 4 years and one return flight ticket to successful applicants.

Eligibility and applying

Applicants must:

  • Be Chinese students with a strong academic background.
  • Students must hold a PR Chinese passport.
  • Applicants can either be resident in China at the time of application or studying overseas. 
  • Students with prior experience of studying overseas (including in the UK) are eligible to apply. Chinese QMUL graduates/Masters’ students are therefore eligible for the scheme.

Please refer to the CSC website for full details on eligibility and conditions on the scholarship.

Applications are invited from candidates with, or expecting to be awarded, at least an upper-second class bachelors degree, or equivalent qualification, in Computer Science, Mathematics, Physics or Materials Science, and a strong interest in interdisciplinary research. A solid familiarity with coding and mathematics is essential. A Master's degree in theoretical/computational subject would be an advantage but not essential. 

Applicants are required to provide evidence of their English language ability. Please see our English language requirements page for details.

The deadline for applications to Queen Mary is 30th January 2022. Applicants will need to complete an online application form by this date to be considered, including a CV, personal statement and qualifications. Shortlisted applicants will be invited for a formal interview by the project supervisor. Those who are successful in their application for our PhD programme will be issued with an offer letter which is conditional on securing a CSC scholarship (as well as any academic conditions still required to meet our entry requirements).

Once applicants have obtained their offer letter from Queen Mary they should then apply to CSC for the scholarship by the advertised deadline with the support of the project supervisor. For September 2022 entry, applicants must complete the CSC application on the CSC website between 10th March - 31st March 2022.

Only applicants who are successful in their application to CSC can be issued an unconditional offer and enrol on our PhD programme.

Apply Online

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