Research Associate (Fixed Term)

at  University of Cambridge

An exciting opportunity has arisen for a highly motivated and talented post-doctoral biostatistician, statistician or researcher in statistical machine learning to join Dr Brian Tom’s group at the MRC Biostatistics Unit, Cambridge University, to develop and apply statistical methodology in the area of precision medicine.
Dr Brian Tom’s group focuses on using longitudinal data and complex phenotypes and endotypes for improved understanding and decision making in medicine. He has a number of collaborations locally, nationally and internationally. His group sits within the Unit’s Precision Medicine Theme that comprises three other groups, which are complementary with significant interactions and cross-fertilisation. The Theme positions itself at the interface between statistical methods and substantive biomedical applications, which allows for innovation and breadth.
Depending on academic background and research interests, the successful applicant could contribute to research areas/projects related to either: (1) dynamic modelling of high dimensional longitudinal and/or functional biomarker processes and clinical outcomes to characterize and understand disease; (2) causal modelling to assess the impact of time-varying exposures and/or treatments on disease course/progression within a multi-state modelling framework; (3) estimating optimal treatment rules and regimes using observational data; or (4) prioritising data types/variables in mixture models for stratification using regression models or model-based clustering. There is flexibility in the inferential framework adopted, including from frequentist, Bayesian, Generalized Bayes/decision-theoretic or hybrid perspectives.
The successful candidate will have a PhD in a strongly quantitative discipline, ideally (bio)statistics or statistical machine learning, with experience in one or more of the following areas: longitudinal data analysis, event history modelling, causal inference and statistical machine learning. Experience with biomedical or epidemiological applications would be highly advantageous, but not essential. A desire to develop statistical methodology and to address questions of substantive biomedical importance is essential. The ability to work as part of a multi-disciplinary team and to communicate clearly and effectively is important. Good statistical programming skills are required, as is a commitment towards open and reproducible science. Training will be given on the basic concepts necessary to the post. The successful applicant will be supported in their career development with a range of courses and on-the-job training.
Fixed-term: The funds for this post are available for 3 years in the first instance.
For an informal discussion about this post, please contact Dr Brian Tom at: brian.tom@mrc-bsu.cam.ac.uk.
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.
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. We welcome applications from those wishing to work part-time or other flexible working arrangements.
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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: 6th October 2024
The interview date for the role is: To be confirmed
Please quote reference SL43127 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

Please refer the Job description for details