Bioinformatician in Spatial Transcriptomics and Single-Cell Genomics

We have an exciting opportunity for a Bioinformatician in Spatial Transcriptomics and Single-Cell Genomics to join the CTAP team. We will characterise the spatiotemporal cellular dynamics of our paediatric patient cohort using high-resolution profiling technologies in conjunction with detailed clinical metadata. We will also integrate these data with existing datasets derived from our adult patient cohorts to better to better assess whether pathophysiological pathways are shared between the paediatric and adult diseases. This project is funded by the Chan Zuckerberg Initiative. As the post-holder you will join the group of Dr Calliope Dendrou at The Kennedy Institute of Rheumatology, and will be closely co-supervised by Prof Holm Uhlig at the Translational Gastroenterology Unit in Oxford.

In this role you will conduct detailed analyses of uni- and/or multi-modal spatial and single-cell omics data and imaging datasets generated – using analysis to identify, define and plan new projects that contribute to the overall aims of the project. You will develop and use novel computational methodologies for interrogating and integrating datasets - creating, testing and implementing version-controlled computer code as required. You will also be responsible for devising novel approaches for data analysis, developing informatics structures to manage large datasets, and contributing to code and data sharing and deposition via appropriate portals. It is also expected that you will prepare manuscripts for publication in high profile peer-reviewed journals, taking leadership in more specialised publications on bioinformatics, and present results at scientific meetings 

To be successful in this role, it is essential that you hold a PhD in Immunology, Bioinformatics, Statistics, Mathematics, Computer Science or other related computational subject. You must have experience in the analysis of spatial transcriptomics data (e.g. generated using Xenium, Visium, Merscope or CosMX), as well as experience in the analysis of single-cell RNA-seq data (e.g. generated using 10X Genomics platforms). You  must demonstrate proficiency with a high-level programming language (Python, R) and/or appropriate scripting languages, and show an ability to deliver high-calibre analytical outputs as evidenced through a strong publication record in high-quality peer-reviewed journals and a high degree of ambition and self-motivation.

It is preferable that you have experience using machine learning approaches, and experience analysing spatially resolves, multi-colour immunofluorescence imaging date. A working knowledge of gastrointestinal tissue biology and immunology, and experience in writing grant protocols or contributing to grant application preparation is desirable but not essential. 

Due to the nature of the research at the Kennedy Institute of Rheumatology, this job will require additional security pre-employment checks:

•    A satisfactory basic Disclosure and Barring Service check 

This is a fixed-term, full time position until 30th November 2026.

A lower grade offer (Grade 7: £36,024- £44,263 p.a.) may be made to a less experienced candidate (such as recent PhD/DPhil graduates) or candidates originally from experimental backgrounds who need further training in Single-Cell Genomics if a suitable candidate cannot be found to fill the Grade 8 position.  

The closing date for this position is 12 noon on Thursday 28th March 2024. You will be required to upload a CV and supporting statement as part of your online application.