EPSRC DLA Studentship with Angstrom AI - Probabilistic Machine Learning
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.
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.
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. Full eligibility criteria can be found via the following link; https://www.postgraduate.study.cam.ac.uk/finance/fees/what-my-fee-status.
To apply for this studentship, please send your two page CV to jmh233@cam.ac.uk to arrive no later than 1 January 2025.
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 applicant portal can be accessed via: www.graduate.study.cam.ac.uk/courses/directory/egegpdpeg. 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.