Research associate in bayesian modelling of gene expression dynamics
university of manchester,uk
The post-holder 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. they will be responsible for developing and applying methods for statistical analysis and modelling of high-throughput sequencing data (incl. rna-seq, chip-seq and ribo-seq) collected in a set of time-series experiments during embryonic development. the post will involve the development and application of bayesian modelling approaches, building on recent developments in gaussian process inference. the post will require close collaboration with experimental researchers generating these datasets and with other computational researchers modelling single-cell resolution live-cell imaging data from the same experimental system.
You will have a phd or equivalent with a significant computational and/or statistical element and experience of probabilistic modelling, bayesian inference and scientific programming. a strong interest in molecular cell 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 information, please visit:
for further details and the application process, see https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=18159