Research Associate (Fixed Term)

The MRC Biostatistics Unit is one of Europe's leading biostatistics research institutions. Our focus is to deliver new analytical and computational strategies based on sound statistical principles for the challenging tasks facing biomedicine and public health.

We are seeking a highly motivated Research Associate in Biomedical Machine Learning, who is passionate about advancing machine learning methodologies. The post holder will develop, apply, and extend state of the art machine learning techniques to generate insights that drive innovation in biomedical science.

Depending on academic background and interests, the successful applicant may contribute to areas including, but not limited to:

Spatio temporal modelling and forecasting (e.g., epidemic dynamics, population-level health trends, video reconstruction)

Robust and principled machine learning approaches inspired by geometry, physics, or domain constraints.

Modelling latent representations of complex biological systems or medical imaging (e.g., genomic time series, molecular dynamics, 4D flow MRI)

Methods may include self-supervised learning, natural language processing, state-of-the-art generative modelling, PDE solvers and related approaches.

The post-holder will be a member of Dr Kyriakos Flouris' research group as well as the broader Biostatistical Machine Learning (BML) research theme at the MRC Biostatistics Unit and will contribute to the local research community by attending and contributing to group, theme and departmental meetings.

The Unit is situated on the Cambridge Biomedical Campus, one of the world's most vibrant centres of biomedical research, which includes the University of Cambridge's Clinical School, two major hospitals, the MRC Laboratory of Molecular Biology, and the world headquarters of Astra Zeneca.

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. Working entirely from the office is possible.

We welcome applications from individuals who wish to be considered for part-time working or other flexible working arrangements.

To apply online for this vacancy and to view further information about the role, please click 'Apply' above.

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.

Please quote reference SL46884 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.

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