Research Associate (Fixed Term)

CWZ256 -please update informal enquiries line

The Wallace group (https://chr1swallace.github.io) work on understanding mechanisms underlying immune-mediated disease through integrated analysis of omics data.

We seek a statistician interested in human genetics who wants to apply machine learning to estimate cell population frequencies from bulk gene expression data. A common approach to identify dysregulated pathways in diseases is to compare gene expression profiles from healthy vs disease samples.  However, the cellular composition of many biological samples is heterogeneous, and, given that many disease processes involve cell infiltration and expansion, such comparisons are confounded by changes in cellular composition. In addition, it is generally recognised that rare populations play a critical role in the pathogenesis of complex diseases, therefore, the ability to measure and interpret phenotypic changes between specific conditions at the cell subset level is critical to obtain a detailed understanding of the role of each cell subset in disease. However, in practice, measuring the frequency of such populations in large cohorts of human samples can be very challenging. Thus, methodologies to infer population frequencies from bulk transcriptome data opens up many possibilities towards understanding disease mechanisms.

We have access to novel datasets that will allow us to address different questions. One area of interest is to infer the proportion of the pathogenic sub-populations of T cells in blood from samples of patients with childhood arthritis which correlate with disease activity. In particular, we are interested in inferring the levels of pathogenic IL-17 T cells and apply those methods to test whether levels of IL-17 affect response to treatment with  IL-17 antagonists in collaboration with GOSH/UCL. Additionally, we will explore whether inferred populations of innate immune cells are predictive of the response to flu vaccine in elderly individuals in collaboration with the Babraham Institute. We will have access to samples from healthy individuals to infer the proportions of rare immune cell populations (collaboration with Oxford). We expect that having access to such a wide variety of datasets will allow us to identify robust methods that can consistently perform well across conditions. Undoubtedly, lessons learned in this work would be useful for a wide range of conditions.

Fixed-term: The funds for this post are available until 31 March 2024 in the first instance. 

Informal enquiries may be directed to Dr Elena Vigorito elena.vigorito@mrc-bsu.cam.ac.uk.

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: 26th February 2023

The interview date for the role is: To be confirmed

Please quote reference SL35185 on your application and in any correspondence about this vacancy.

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