Postdoctoral Fellow in GBM Spatial Multi-omics

The opportunity:

The Bayraktar group is seeking a 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 team:

The Bayraktar group studies the cellular wiring of human tissues using spatial genomics, focusing on brain development and disease. Our highly collaborative and international team has expertise in single cell/spatial genomics, microscopy and multi-modal data analysis. The GBM-space project led by Dr. Bayraktar brings us together with other experts in bioinformatics, cancer and neurodevelopment across Cambridge, DFKZ and the Crick.

About the role/you:

You will generate exciting single cell and spatial genomic datasets of GBM, drive data interpretation and design for your own project for validation or functional follow-up. You will perform single nuclei multi-ome (10X joint snRNA-ATAC-seq) profiling of human GBM resection tissue samples, supported by our wet-lab team. You will be responsible for the biological interpretation of our integrated single cell and spatial genomic datasets, working closely with computational scientists to identify TME-GBM interactions and malignant cell trajectories. You will develop follow-up projects for orthogonal validation (in situ sequencing, 3D tissue imaging) or functional studies (patient-derived cell lines, high content screens, PDX models) using technologies available through our group and our local collaborators.

You should have a track record in cancer biology and a strong interest in neural development. Experience with single cell / spatial genomic or high-throughput functional assays is desirable. We are looking for an independent individual who can craft their own projects, yet work with our diverse wet and dry lab staff to accomplish our large-scale and collaborative scientific goals. 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).

Transcriptome-wide spatial RNA profiling maps the cellular architecture of the developing human neocortex. Roberts K, Aivazidis A...Hemberg M, Bayraktar OA. bioRxiv 2021 https://doi.org/10.1101/2021.03.20.436265

Astrocyte layers in the mammalian cerebral cortex revealed by a single-cell in situ transcriptomic map. Bayraktar OA*, Bartels T…Geschwind DH, Rowitch DH*. Nature Neuroscience 2020.

Job Logo
Athena Swan
Grade
PDF
Salary per annum
32,780-41,093
Full Time, Part Time, Flexible Working
Full Time/Flexible working considered
Contract Type
Fixed Term
Contract Length
36 months
Closing Date
5 December 2021
Job Reference
84530

Essential Skills

Technical Skillset

  • PhD in relevant wet-lab subject (e.g. Molecular Biology, Cancer, Developmental biology) 
  • Background in cancer biology including proven track record (publications and conference presentations) 
  • Experience in practical molecular biology and sequencing applications 
  • Experience with managing/responsibility for scientific projects 
  • Ability to test, implement and troubleshoot new approaches and techniques 

Competency/Behavioural Skillset

  • 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 

Ideal Skills

Technical Skillset

  • Experience in single cell, spatial genomics or high-throughput functional assays

Other information

Application Process:

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: