Computational Biologist, Spatial Transcriptomics

Другое

• Company Bio is producing matched spatial transcriptomics, histopathology images and clinical datasets from real patient tumours. We’re looking for a computational biologist to own post-run QC and secondary analysis of our Xenium data, from transcript-level and cell-feature outputs through to datasets aligned with post-run H&E images.
• Develop reproducible QC workflows for transcript detection, background signal, cell segmentation, transcript assignment, tissue and imaging artefacts, and variation across samples and runs.
• Align post-run H&E whole-slide images to Xenium DAPI images and assess registration accuracy across each tissue section.
• Work with pathologists to bring tumour regions and other histological annotations into the spatial data.
• Analyse the data beyond cell typing: investigate cell states, spatial neighbourhoods, tumour–immune interactions, differential expression and other patterns that emerge from the tissue. Use relevant single-cell reference datasets where helpful.
• Identify meaningful questions that require analysis of the data to answer. For selected questions, derive well-supported reference results and turn the work into reproducible tasks that evaluate whether AI models can reach those results from the underlying data.
• PhD or postdoctoral research in spatial biology or equivalent hands-on industry experience. Xenium or CosMx experience is especially valuable; experience with other spatial platforms is welcome.
• Analysis of oncology tissue, H&E whole-slide images, or multiple imaging modalities such as IHC and immunofluorescence.
• Strong Python or R skills and experience building reproducible analysis workflows.
• Experience with scRNA-seq or bulk RNA-seq analysis, including the use of reference data to interpret spatial measurements.
• Sound statistical judgement: recognising noise, batch effects, experimental artefacts and confounding variables, and knowing when an apparent biological finding needs further validation.
• This is a full-time role. We prefer someone who can work with us in person in San Francisco, but we’re open to the right person working remotely.