|Funding for:||UK Students, EU Students, International Students|
|Placed On:||28th February 2023|
|Closes:||3rd April 2023|
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 . In our research, we have designed a deep neural network that can also learn an ensemble of structures of specific proteins from molecular simulations . 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 www.degiacomi.org and cwkx.github.io
 J. Jumper et al., Highly accurate protein structure prediction with AlphaFold, Nature 596, 2021.
 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
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
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