PhD Studentship in Learning protein dynamics

at Durham University
Published March 1, 2023
Location Durham, United Kingdom
Category Machine Learning  
Job Type Scholarship  


Number of awards


Start date and duration October 2023 3.5 years


100% tuition fees paid and annual living expenses of £17,668

Deadline 3rd April 2022

Overview The Degiacomi group at Durham University is offering a studentship in the area of machine learning for computational biophysics.

All living organisms contain millions of proteins; biopolymers that fold into three-dimensional biologically active structures playing a vital role in the regulation of life and diseases. Research has seen a lot of focus on determining the atomic structure of different proteins. However, the flexible movement of these biopolymers plays a crucial role in their biological (mal)function.

In recent years, machine learning has been revolutionizing the way we interpret data in many scientific areas. For example, the deep neural network AlphaFold2 can predict the 3-diminsonal structures of proteins, whose shape is not known experimentally [1]. In our research, we have designed a deep neural network that can also learn an ensemble of structures of specific proteins from molecular simulations [2].  This project builds upon this breakthrough.

In collaboration with the Willcocks group (Department of Computer Science), you will develop a general neural network capable of learning and predicting the dynamics of any protein. The neural network will be trained with existing and new data you will produce from molecular dynamics simulations. Applications of this work are vast, ranging from understanding the effect of genetic mutations in cancers to informing the design of proteins to carry out a desired function.

Further information on the research of the Degiacomi and Willcocks groups can be found at and

[1] J. Jumper et al., Highly accurate protein structure prediction with AlphaFold, Nature 596, 2021.

[2] V.K. Ramaswamy, S.C. Musson, C.G. Willcocks, M.T. Degiacomi. Learning protein conformational space with convolutions and latent interpolations, Physical Review X 11, 2021.

The department is committed to promoting diversity, and we particularly encourage applications from under-represented groups.

Sponsor Engineering and Physical Sciences Research Council (EPSRC)

Name of supervisor(s) Dr Matteo Degiacomi

Eligibility Criteria

You must have or expect a First Class honours Bachelor's degree, or at least a 2:1 Integrated Master’s degree or a Master's degree in an physics, computer science, chemistry, biology, or related discipline, from a recognised university (or equivalent).

Applications are open to Home and international/EU candidates. If English is not your first language, you must have IELTS 6.5 overall (with a minimum of 6 in all sub-skills).

How to apply

You must apply through the University’s applicant portal

You will need to:

  • State CMP Degiacomi in the 'Field of Study' section.
  • On the funding tab select ‘yes’ you are applying for a scholarship, select ‘PGR-Research Council Studentships’
  • attach a covering letter and CV
  • provide a short research proposal of a few paragraphs (no longer than 1 page) detailing your research interests.
  • attach degree transcripts and certificates and, if English is not your first language, a copy of your English language qualifications.
  • provide 2 referee contact details (specifically email addresses) who we will contact directly.


For informal enquiries please contact