You will join a team of computational, mathematical and experimental biologists funded by a Wellcome Trust programme investigating spatial patterns and temporal processes with single-cell resolution. You will be responsible for developing and applying methods for machine learning and probabilistic modelling of high-throughput sequencing data and high-resolution imaging data collected during embryonic development. The post will involve the development and application of innovative methods, building on the group’s recent work in Gaussian processes, hidden Markov models and deep learning. You will have a PhD (or equivalent) with a significant computational and/or statistical element and will have experience of probabilistic modelling and/or machine learning. A strong interest in molecular biology is essential. You should also have a good scientific publication record given career stage and be self-motivated, hard-working and able to work in a team.
The School is strongly committed to promoting equality and diversity, including the Athena SWAN charter for gender equality in higher education. The School holds a Silver Award which recognises their good practice in relation to gender; including flexible working arrangements, family-friendly policies, and support to allow staff achieve a good work-life balance. We particularly welcome applications from women for this post. All appointment will be made on merit.
For further details and application process see www.jobs.manchester.ac.uk/displayjob.aspx?jobid=19928
PhD in subject with significant computational or statistical element
Apply via website www.jobs.manchester.ac.uk/displayjob.aspx?jobid=19928