Spatial Omics Postdoc Fellow (2-Year, Hybrid)

Emerging Scholars Council; Edinburgh (IN); Hybrid; USD 55,000 - 70,000; Full time

Job summary

Emerging Scholars Council is seeking a Post-Doctoral Research Fellow to join the Guest Lab at the Institute of Genetics and Cancer for a 2-year funded project. You will lead spatial multi-omics and single-cell transcriptomics on tissue from transgenic mouse models, collaborating with Keio University on MALDI-MSI.

The role emphasizes computational integration of spatial metabolomic and transcriptomic data, in vivo tissue processing, and developing the analysis pipeline.

Qualifications

• Strong computational and bioinformatics skills for high-dimensional data (transcriptomics, metabolomics).
• Experience with mouse models, tissue harvesting, processing, and cryosectioning is required.
• Experience with spatial omics technologies and/or scRNA sequencing is highly beneficial.
• PhD (or near submission) in bioinformatics, computational biology, systems biology, cancer biology, or related field.
• Ability to work in an international, multidisciplinary team.

Responsibilities

• Lead the spatial multi-omics component of the programme, performing spatial and single-cell transcriptomics on tissue from transgenic mouse models.
• Collaborate with Keio University for MALDI mass spectrometry imaging (MALDI-MSI) of spatial metabolomics.
• Develop and optimise the spatial analysis pipeline and contribute to high-impact publications.
• Contribute to in vivo work including tissue harvesting and processing.

Skills

Bioinformatics

R/Python

Mouse models

Spatial omics

Team collaboration

Education

PhD (or near submission)

Tools

10x Visium

MERFISH

MALDI-MSI

Job description

Emerging Scholars Council is seeking a Post-Doctoral Research Fellow to join the Guest Lab at the Institute of Genetics and Cancer for a 2-year funded project. You will lead spatial multi-omics and single-cell transcriptomics on tissue from transgenic mouse models, collaborating with Keio University on MALDI-MSI.

The role emphasizes computational integration of spatial metabolomic and transcriptomic data, in vivo tissue processing, and developing the analysis pipeline.