We have just advertised an exciting and unusual new job. Normally, advertised posts in our team are to work on the various specific projects where we already have funding. A fellowship is something different: this is traditionally an academic post where the applicant brings their own plans for work that they themselves have devised; they also bring their own funding.

On this occasion, the funding work is done for you: following a generous philanthropic gift from the Peter Bennett Foundation we are now advertising a fully funded three year Junior Research Fellowship based at Jesus College, Oxford (where our Director is a Professorial Fellow).

As well as working with our amazing, friendly team, you’ll get all the benefits of college affiliation, including office space in Jesus College, accommodation (a single Fellow may rent furnished rooms, if available), dining rights, membership of the Senior Common Room, research allowance or £1000 per year, and access to a Major Research Grants Fund.

There are two keys to a successful application for a post like this. The first is your excellent prior work in the field. The second, for a fellowship, is the proposed programme of work.

For this, it’s important to find a good fit. The Bennett Institute follows a different model to some other groups. We are a mixed team, with traditional researchers working closely alongside professional software developers from outside academia. We are interested in building methods, platforms and tools that make data useful, as much as single academic analyses on single research questions. We like finding policy barriers to better use of data, then fixing them. And we are interested in practical uses of data to improve the lives of patients and citizens, beyond academic publications alone.

We’re looking for someone who is excited to work in this way, with our team, perhaps by using or expanding our tools like OpenSAFELY, OpenPrescribing and TrialsTracker.

Specific examples of the kind of work you might propose include:

  • Delivering high quality epidemiology research in large electronic health record datasets, but specifically doing this by developing and using tools and methods that optimise reproducibility, privacy, efficiency and quality.
  • Developing and evaluating methods and tools to protect patients’ privacy when analysing large disclosive datasets (eg with OpenSAFELY).
  • Optimising the adoption of open methods and open code in research.
  • Optimising the regulation of research and digital health.
  • Optimising reproducibility of research and unbiased clinical trial reporting (e.g. with TrialsTracker).
  • Optimising the use of data for health service monitoring and improvement (e.g. with OpenPrescribing)

This is an exceptional post, and we look forward to seeing your application!

Full details, including how to apply are at the link below: