PhD Studentship in AI for Protein Modelling

One fully funded, full-time PhD position to work with Dr. Matteo Degiacomi at the School of Informatics, University of Edinburgh. The aim of this project is the development of AI-based solutions to study biomolecular structure, dynamics, and assembly. The PhD candidate will address the inverse problem of rationalising experimental data on proteins and their assemblies by generating ensembles of atomic models.

Proteins are large molecules that, by folding into specific three-dimensional shapes, can interact with specific binding partners such as drugs, DNA, or other proteins. While these interactions are key for life as we know it, they are also associated with diseases and disorders. For this reason, nowadays the understanding of illnesses and the design of new therapies are often driven by the determination of the atomic structure of proteins. As shown by this year’s Nobel Prize in Chemistry, the recently demonstrated ability of AI to predict the three-dimensional structure of proteins can be extremely impactful in this context. Building upon machine learning models and software developed in the Degiacomi group and others (e.g., molearn, BOLTZ-1, BioEmu, …), the PhD candidate will develop methods to rationalise experimental data yielded by experimental techniques (e.g., mass spectrometry, small-angle x-ray scattering), reporting on proteins structure, dynamics, and assembly.

Candidate’s profile

• A good Bachelors degree (2.1 or above or international equivalent) and/or Masters degree in a relevant subject (physics, mathematics, engineering, computer science, or related subject)
• Proficiency in English (both oral and written)
• Practical knowledge machine learning frameworks (e.g. PyTorch)
• Previous experience with manipulation of biomolecular experimental data and/or protein structures is highly desirable

Studentship and eligibility

The School funded studentship covers:

• Full time PhD tuition fees for a student with a Home fee status (£4,786* per annum) or Overseas fee status (£33,100 per annum)
• A tax-free stipend of GBP £19,237* per year for 3.5 years
• Additional programme costs of £1,000 per year

*Rates are for 24/25 as 25/26 rates not yet confirmed

Application Information

Applicants should apply via the University’s admissions portal (EUCLID) and apply for the following programme postgraduate.degrees.ed.ac.uk/index.php?r=site/view&edition=2024&id=489 with a start date 01/09/2025.

Applicants should state “AI for protein modelling” and the research supervisor (Matteo Degiacomi) in their application and Research Proposal document.

Candidates are encouraged to submit their completed application as early as possible. Applications will be considered until the 1^st March 2025, or the position is filled.

The anticipated start date is 01/09/2025 but earlier/later start dates can be considered.

Applicants must submit:

• All degree transcripts and certificates (and certified translations if applicable)
• Evidence of English Language capability (where applicable)
• A short research proposal highlighting how past interests and experience match this position (max 2 pages)
• A full CV and cover letter describing your background, suitability for the PhD, and research interests (max 2 pages)
• Two references (note that it the applicant’s responsibility to ensure reference letters are received before the deadline)

Only complete applications (i.e., those that are not missing the above documentation) will progress forward to Academic Selectors for further consideration.

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