Research Associate*/Research Assistant in Biomedical Data Science

Research Grade 5: £32,546 - £35,116

Research Grade 7*: £37,174 - £45,413

We are seeking a talented biomedical or health data scientist to join our team as a postdoctoral researcher in the Cardiovascular Epidemiology Unit (CEU) and Cambridge Baker Systems Genomics Initiative (CBSGI) of the Department of Public Health and Primary Care (DPHPC). The post will suit researchers interested in analysing genomic, mult-omic and phenotypic/health-record data at population-scale (>>1 million individuals) using the CEU's broad portfolio of different cohorts.

The primary role of the post holder will be to lead projects involving the quantitative analysis and interpretation of genomic, multi-omic and phenotypic data using polygenic scores, GWAS, Mendelian randomisation, and other statistical and machine-learning methods. The appointed researcher will have research interests aligned with those of our groups and the freedom to develop their own ideas for new research by contributing to the preparation of new grant applications. Initial possibilities for research projects include:

  • Integrating multi-omics data to dissect the molecular etiology of cardiometabolic diseases
  • Leveraging biochemical knowledge and databases (e.g. REACTOME) to model and interpret multi-omics data and complex phenotypes
  • Combining genetics and structural bioinformatics to understand variant-to-function and potentially improve therapeutic outcomes

The post-holder will be expected to evaluate and develop the statistical methods necessary to test hypotheses of interest, such as those listed above and advise on appropriate statistical practices. However, we are also open to exploring other research questions and proposals from candidates that could be addressed using datasets available to us locally or through collaboration. The work of the post-holder is expected to lead to first author high-impact publications.

The preferred candidate will have a PhD in one of the following subjects: Statistical Genetics, Biostatistics, Bioinformatics, Statistics, Computer Science, Mathematics or similar or equivalent experience. They will have in-depth knowledge of and demonstrated experience in statistical genetics, strong quantitative (in silico) analysis skills using statistical programming packages such as R or similar, and experience working on computing clusters/computers running Linux based operating systems.

Appointment at Research Associate level is dependent on having a PhD (or equivalent experience), including those who have submitted but not yet received their PhD. Where a PhD has yet to be, awarded appointment will initially be made at research assistant and amended to research associate when the PhD is awarded (PhD needs to be awarded within 6 months of the start date)

This position is available full-time or part time (0.8FTE) immediately for the duration of 2 years from commencement in post.

We strongly value and encourage Equity, Diversity and Inclusion as well as a flexible working environment.

If you have any questions about this vacancy or the application process, please contact Professor Michael Inouye mi336@medschl.cam.ac.uk

Location of post: Victor Phillip Dahdaleh Heart & Lung Research Institute, Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Biomedical Campus, Papworth Road, Trumpington, Cambridge CB2 0BB

Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.

Closing date: 29th April 2025

Interview date: week commencing 12th May 2025

Please ensure that you upload a covering letter and CV in the Upload section of the online application. The covering letter should outline how you match the criteria for the post and why you are applying for this role. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application.

Please include details of your referees, including email address and phone number, one of which must be your most recent line manager

For information about how your personal data is used as an applicant, please see the section on Applicant Data (https://www.hr.admin.cam.ac.uk/hr-staff/hr-data/applicant-data) on our HR web pages.

Please quote reference RH45651 on your application and in any correspondence about this vacancy.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.