This is a competition funded project through the NERC GW4+ DTP. There is a competitive selection process. This studentship will cover fees, stipend and research costs for UK students and UK residents for 3.5 years.
Candidates should have an interest in computational biology, and be able to demonstrate experience in previous projects that require some level of programming and/or scripting. Suitable candidates from all STEM backgrounds will be considered. It is important to have an interest in biological problems, but no formal training in biology or genomics is required.
Beaumont, M. A. (2019). Approximate Bayesian computation. Annual review of statistics and its application, 6, 379-403.Heine, K., Beskos, A., Jasra, A., Balding, D., & De Iorio, M. (2018). Bridging trees for posterior inference on ancestral recombination graphs. Proceedings of the Royal Society A, 474(2220).Mondal, M., Bertranpetit, J., & Lao, O. (2019). Approximate Bayesian computation withdeep learning supports a third archaic introgression in Asia and Oceania. Nature communications, 10(1), 246.Schraiber, J. G., & Akey, J. M. (2015). Methods and models for unravelling human evolutionary history. Nature Reviews Genetics, 16(12), 727.Vehtari, A., Gelman, A., Sivula, T., Jylänki, P., Tran, D., Sahai, S., Blomstedt, P., Cunningham, J.P., Schiminovich, D. and Robert, C., 2019. Expectation propagation as a way of life: A framework for Bayesian inference on partitioned data. arXiv:1412.4869.
FTE Category A staff submitted: 64.60
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