Research Associate in Biostatistics

University of Cambridge

A position is available in Hélène Ruffieux's team at the MRC Biostatistics Unit, Cambridge University for a talented statistician to work on the development of methodology related to Bayesian inference in the context of biomedical research.

The post holder will develop hierarchical modelling and scalable inference approaches to uncover dependence structures and temporal dynamics from complex clinical and molecular data (e.g., genetics, transcriptomics, proteomics, metabolomics) in order to advance our understanding of disease risk and progression. They will contribute to the team's research, which focuses on exploiting shared information across related traits, conditions or timepoints, using Bayesian joint modelling (based on functional principal component analysis, Gaussian graphical modelling, variable selection or sparse regression) and tailored approximate inference algorithms (based on variational Bayes or other fast posterior inference procedures). The developed methodology will be used in ongoing collaborations with biologists and clinicians in the UK and abroad.

The MRC Biostatistics Unit is a leading centre of biostatistics research in Europe, located in Cambridge and part of the University. It hosts five research programmes undertaking research on statistical methods and their application to the design, analysis and interpretation of biomedical studies, with the aim to respond to current and future scientific needs in health and biomedicine. The Unit offers an excellent environment in which to develop a career.

Applicants will have, or be close to completing a PhD in Biostatistics, Statistics, Computational Biology, Machine Learning or a closely aligned discipline. They should have a strong background in Bayesian statistics and computation, as well as good computational and software development skills (e.g., proficient in R, Julia, Python, git). Experience with biomedical applications would be highly advantageous, but not essential. The successful applicant will have a creative approach to problem-solving, as well as excellent time management and communication skills, including the ability to write for publication, present research proposals and results, and represent the research team at meetings. An enthusiasm for collaborating with others is essential.

This post offers opportunities to publish in high-quality scientific journals, and build collaborations with researchers across the Cambridge Biomedical Campus and beyond. Career development support will be provided, with different formal courses and on-the-job training.

The Unit is actively seeking to increase diversity among its staff, including promoting an equitable representation of men and women. The Unit therefore especially encourages applications from women, from minority ethnic groups and from those with non-standard career paths. Appointment will be made on merit.

The Biostatistics Unit is committed to supporting hybrid working for all staff, but we do expect that staff will work from the office on a regular basis to help integration and to build our fantastic scientific community. If you'd prefer to work entirely from the office that is great too.

We welcome applications from those wishing to work part-time.

For more information about this post, please contact Dr Hélène Ruffieux,

Fixed-term: The funds for this post are available for 2 years in the first instance.

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Please ensure that you upload a covering letter and a 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.

The closing date for applications is: 27th August 2023

The interview date for the role is: To be confirmed

Please quote reference SL37863 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.

Further information

Apply online