Postdoctoral Data Scientist

We are seeking a creative and enthusiastic data scientist or bioinformatician to join an exciting project to uncover patterns of genetic alterations associated with treatment susceptibility in prostate cancer. The project is funded by a recent Prostate Cancer UK award to identify translational results in data compiled by the Pan Prostate Cancer Group (www.panprostate.org), a worldwide initiative to bring together multiomic data from sites across the world. The outputs of this project will pave the way for treatments to be targeted to subsets of patients who will benefit the most, leading to improved outcomes for patients while minimising unnecessary treatments and associated side effects. The position will be based at Old Road Campus, Oxford, but you may be able to agree a pattern of regular remote working with your line manager.

Your primary responsibility will be to analyse our expansive multiomic prostate cancer data set and identify features that enable integration with more limited data arising from clinical trials. You will therefore need strong programming and data analysis skills, with proficiency using machine learning methods. You should be willing to learn and apply both bioinformatics and machine learning methods to curate and compare disparate data sets from different sources. You will be comfortable working independently, while also contributing ideas and communicating results to collaborators across the wider research project.
You will have completed, or be near completion of, a PhD/DPhil in Mathematics, Statistics, Computer Science, Bioinformatics, Physics, Engineering, or a related discipline. You will have the ability to develop academic publications, evidenced through a track record of contributing to publications and presentations.
Previous experience in advanced machine learning approaches for tabular data, familiarity with bioinformatics tools for processing DNA or RNA sequencing outputs, and knowledge of cancer biology, genetics, and evolution would be desirable.