Research Assistant (Fixed Term) at University of Cambridge

An opportunity has arisen for a talented statistician or machine learning methods developer/practitioner to work with Elena Vigorito in the Wallace group (https://chr1swallace.github.io) at the MRC Biostatistics Unit (BSU). The main interest of the group is to develop statistical methods to understand mechanisms underlying immune-mediated disease.

The successful applicant will apply machine learning to estimate cell population frequencies from bulk gene expression data. The key idea is to infer cellular composition exploiting known or learnt gene expression signatures that define particular cell types. This will allow us to monitor rare pathogenic cell populations in patient samples which may inform treatment response in complex diseases. In practice, measuring the frequency of rare populations can be very challenging. Thus, methodologies to infer population frequencies from bulk transcriptome data opens up many possibilities towards understanding disease mechanisms.

The successful applicant will have a Degree and MSc in a strongly quantitative discipline (or close to completion) and the desire to address questions of substantive biological importance and disease relevance.  Experience with biomedical applications would be advantageous but not essential. We expect the successful applicant to be knowledgeable of machine learning and to have good programming abilities. We anticipate this project will include collaboration with researchers at Great Ormond Street, Oxford University and the Babraham Institute, allowing the successful applicant to build their scientific network, and the successful applicant will be supported in their career development with a range of formal courses and on-the-job training.

For an informal discussion about this post please contact Elena Vigorito (elena.vigorito@mrc-bsu.cam.ac.uk). 

Fixed-term: The funds for this post are available until 31 March 2024 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: 25th June 2023

The interview date for the role is: To be confirmed

Please quote reference SL36925 on your application and in any correspondence about this vacancy.

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