We aim to answer questions such as what is the probability that a drug molecule binds a target protein? The molecule equilibrium probability is given by the well-known Boltzmann distribution. Existing methods based on molecular dynamics struggle to generate accurate and independent samples from Boltzmann distributions, especially in high dimensions. We will address this by using advances in deep learning and generative modelling. We will collaborate with the startup Angstrom AI.
About you
Applicants for this studentship should have, or be expected to gain, a high 2:1, preferably a 1st class honours degree in Computer Science or Engineering. A good knowledge of Bayesian statistics, scientific programming and experience with deep learning tools such as Jax or PyTorch.
Further information
EPSRC DLA studentships are fully-funded (fees and maintenance) for students eligible for Home fees. EU and international students may be considered for a small number of awards at the Home fees rate.
Please note that any offer of funding will be conditional on securing a place as a PhD student. Candidates will need to apply separately for admission through the University's Graduate Admissions application portal; this can be done before or after applying for this funding opportunity. The funding is conditional on submitting this application before 31 March 2025.
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.