Postdoctoral Research Assistant in Statistical and Population Genetics (2 posts)
Applications are invited for two full-time Postdoctoral Research Assistant positions in Statistical and Population Genetics in the research group of Professor Pier Palamara, funded by the European Research Council and the US National Institute of Health. The post is fixed-term until 1 April 2022, with a possibility of extension if appropriate. It will involve working within a collaborative group of leading researchers based in Oxford, Harvard Medical School, and elsewhere.
The postdoctoral research assistant will be responsible for developing novel statistical models and machine learning algorithms and applying these to analyse large genomic data sets, such as the UK Biobank and other modern genomic data sets of similar scale. We are particularly interested in models and inference algorithms for genealogical processes (see e.g. Palamara et al. Nature Genetics 2018, https://doi.org/10.1038/s41588-018-0177-x) and in addressing a wide range of open problems in the following research areas: the study of past historical and demographic events, such as population size variation and migration across human populations, using both modern and ancient DNA samples; the study of natural selection, including selection acting on human complex traits and diseases; the study of the genetic architecture of complex traits and diseases, such the distribution, functional role, and evolutionary history of genomic variants involved in heritable traits; methods to perform phenotypic prediction and association between genomic variants and heritable traits in samples of heterogenous ancestry.
The postholder will have access to state-of-the-art data sets and world-leading expertise in human genomic research. The successful applicant will have the skills and ability to conduct high-quality research for publication in high-profile international journals, develop their own research questions, and present their work at conferences and workshops. Applicants must hold or be close to completing a doctorate in a relevant area such as statistics, machine learning, computer science, statistical or population genetics, or mathematics. The successful candidate will have experience of developing novel algorithmic approaches and working with low-level computing languages such as C/C++.
Queries about the post should be addressed to Professor Pier Francesco Palamara (email@example.com)
This post is fixed-term until 1 April 2022 in the first instance.
Only applications received before 12.00 midday on 19 March 2020 will be considered. Interviews will be held on 31 March 2020.