Computational Postdoctoral Fellow in GBM Spatial Multi-omics
The Bayraktar and Stegle groups are seeking a computational postdoctoral fellow to explore how the tumour microenvironment (TME) drives malignant cell states in glioblastoma (GBM) using large-scale spatial multi-omics. Our exciting “GBM-space” project brings together an international collaboration funded by Wellcome LEAP to integrate single cell transcriptomics, epigenomics and spatial RNA/DNA-sequencing to systematically deconstruct TME-GBM cell interactions and plasticity in situ.
The Bayraktar group studies the cellular wiring of human tissues using spatial genomics, focusing on brain development and disease. The Stegle group is interested in computational methods to unravel the genotype–phenotype map on a genome-wide scale. Our collaborative teams have significant expertise in single cell and spatial genomics and multi-modal data integration. The GBM-space project led by Dr. Bayraktar brings us together with other experts in cancer and neurodevelopment across Cambridge and the Crick.
About the role/you:
You will be jointly supervised by Drs. Stegle and Bayraktar to work with exciting multi-omic datasets of human GBM tissue samples. You will apply statistical inference and machine learning tools to develop new computational methods at the frontier of single cell and spatial genomics. These include new methods to integrate large-scale single cell and spatial transcriptomics data to map cellular interactions, and to infer gene expression regulatory programmes and cellular trajectories from single nuclei multi-ome data (10X joint snRNA-ATAC-seq). You will be embedded in both research groups with strong links with the Stegle group at the German Cancer Research Center (DFKZ).
You should have a strong background in statistics/computational biology and a keen interest to work with multi-modal genomic data. Experience with single cell / spatial genomics and machine learning tools are desirable. We are looking for an independent individual who can drive their own projects, yet collaborate closely with our diverse wet and dry lab team. You are expected to play a vital role in writing up studies. You will be embedded in a world-leading and multidisciplinary research environment and become a valued member of our team.
Relevant publications of the team:
Cell2location maps fine-grained cell types in spatial transcriptomic data. Kleshchevnikov V, Shmatko A….Stegle O*, Bayraktar OA*. bioRxiv 2020 https://doi.org/10.1101/2020.11.15.378125 (Nature Biotechnology in press).
Identifying temporal and spatial patterns of variation from multi-modal data using MEFISTO. Velten B, Braunger J... Stegle O. bioRxiv 2020 https://doi.org/10.1101/2020.11.03.366674 (in press)
Multi-Omics Factor Analysis - a framework for unsupervised integration of multi-omics data sets. Argelaguet R, Velten B... Stegle O. Molecular systems biology 2018, 14(6), e8124.
- PhD in relevant quantitative discipline (e.g. Computational Biology, Genetics, Bioinformatics, Physics, Engineering or Mathematics)
- Proven understanding and experience in the fields of genomics, data processing and high-throughput data analysis
- Experience with single cell / spatial genomics and machine learning tools
- Good publication record
- Motivation and ambition to make a personal contribution to GRL research
- Excellent communication skills to allow efficient interactions with collaborators
- Team player with the ability to work with others in a collegiate and collaborative environment
- Ability to effectively prioritise, multi-task and work independently
- Demonstrates inclusivity and respect for all
Please apply with your CV and a Cover letter outlining your suitability for the role addressing the criteria set out above and in the job description.
This is a rolling advert, we will consider applications and hold interviews on an ongoing basis so the role may close early if a successful appointment is made.
Please see video below for more about our research:
You can find out more about being a Postdoctoral Fellow with us here.