Spatial Transcriptomics Scientist — Remote-friendly

Origin; San Francisco (CA); Hybrid; USD 120,000 - 170,000; Full time

Job summary

Origin Bio seeks a computational biologist to own post-run QC and secondary analysis of Xenium data, from transcript-level outputs to datasets aligned with post-run H&E images.

You will develop reproducible QC workflows, align histology images, and work with pathologists to annotate tissue regions, while exploring cell states, spatial neighborhoods, and tumour-immune interactions across samples.

Qualifications

• PhD or postdoctoral research in spatial biology or related field.
• Experience with Xenium or CosMx; other spatial platforms welcome.
• Experience analyzing oncology tissue, H&E slides, or multiple imaging modalities.
• Strong Python or R skills and reproducible analysis workflows.
• Experience with scRNA-seq or bulk RNA-seq, with reference data for spatial interpretation.
• Good statistical judgement: noise, batch effects, artefacts, confounding factors.

Responsibilities

• Develop reproducible QC workflows for transcript detection, background signal, cell segmentation, transcript assignment, tissue and imaging artefacts, and sample-to-sample variation.
• Align post-run H&E whole-slide images to Xenium DAPI images and assess registration accuracy across tissue sections.
• Collaborate with pathologists to bring tumour regions and histological annotations into the spatial data.
• Analyze data beyond cell typing: cell states, spatial neighbourhoods, tumour-immune interactions, differential expression, and other patterns.
• Identify meaningful questions and derive reference results that test AI model capabilities from the data.

Skills

Python

R

Reproducible workflows

Single-cell RNA-seq

Bulk RNA-seq

Statistics

Spatial biology

Education

PhD in spatial biology or related field

Tools

Xenium

CosMx

Spatial platforms

Job description

Origin Bio seeks a computational biologist to own post-run QC and secondary analysis of Xenium data, from transcript-level outputs to datasets aligned with post-run H&E images.

You will develop reproducible QC workflows, align histology images, and work with pathologists to annotate tissue regions, while exploring cell states, spatial neighborhoods, and tumour-immune interactions across samples.