Postdoctoral fellow

 
  • EMBL
  • United Kingdom
  • Jan 13, 2022
Science Full Time - Fixed Term

Job Description:

We are seeking a talented and highly motivated postdoctoral fellow to join the Marioni laboratory and use single-cell genomics data to construct and compare senescence trajectories for cells.

This project is part of the new NIH-funded Cellular Senescence Network Consortium (SenNet). You will be based at the EMBL-EBI in Hinxton working as part of a larger collaboration with investigators predominantly based in the US.

The Marioni group is a world leader in computational biology, with a particular interest in developing methods that exploit high-throughput single cell genomics data to understand the molecular mechanisms that underpin decision making in cells in the context of normal development and cancer. The lab has contributed some of the most influential papers in the field of single cell genomics, including key methodological advances that have underpinned numerous scientific insights. John Marioni is also a key member of the teams leading development of the NIH funded Human BioMolecular Atlas Program Consortium (HuBMAP) and the international Human Cell Atlas project (HCA). This project will build on the success of these ongoing collaborations and, importantly, will enable the specific identification and prioritisation of senescent cells that may be poorly represented in standard healthy reference atlases.

The successful candidate will have a strong background in computational biology, with a PhD in a relevant discipline. They will also have excellent communication skills and a genuine interest in applying computational methods to biological questions.

The aim of this project is to develop and utilise computational methods for constructing and comparing trajectories of senescence using single-cell genomics data. A key challenge will be to compare these trajectories between cell types, using Dynamical Time Warping and Gaussian Process-based methods, to determine whether the rate of senescence varies between cell types. This will allow identification of cell types that senesce at different rates and whether these rates vary across different molecular features (e.g., chromatin accessibility and gene expression).

Another possible project is to develop methods for understanding what extrinsic features might drive these differences (e.g., does an organ have a metabolic function?) and to predict early senescing cells. To do this we will use linear modelling based strategies, enabling proper accounting for confounding effects.

It will be important to link with the other consortium partners to ensure that any findings are tested experimentally, thereby complementing the analysis and experimental parts of SenNeT.

Methodologies and data will be transferred between SenNeT partners as and when needed. Some travel to the US (pandemic allowing) will be required.

You will:



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At EMBL-EBI you can apply your talent and passion to accelerate science and tackle some of humankind's greatest challenges. EMBL-EBI, part of the European Molecular Biology Laboratory, is a worldwide leader in the storage, analysis and dissemination of large biological datasets. We provide the global research community with access to publicly available databases and tools which are crucial for the advancement of healthcare, food security, and biodiversity. Join a culture of innovation
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