Senior Bioinformatics Scientist

About the role

We seek a Senior Bioinformatics Scientist to own and develop the methods and pipelines that power our proprietary capsule platform and feed our Universal Virtual Cell-Signaling Model. Working across single-cell, spatial, and bulk RNA-seq, you'll build reproducible pipelines, develop new bioinformatics methods, and apply them to our data. You'll collaborate closely with wet lab scientists, software engineers, and machine learning researchers to advance novel sequencing protocols and our therapeutic programs. This is a hands-on role spanning single-cell and spatial omics, ideal for someone who thrives in a fast-paced, interdisciplinary environment and wants to help build our cell-replacement therapy platform from the ground up.

Responsibilities

• Develop new bioinformatics methods for single-cell, spatial, and bulk transcriptomics data, and adapt and benchmark existing ones.
• Build and maintain reproducible analysis pipelines for single-cell, spatial, and bulk RNA-seq, from QC and normalization through the downstream analysis appropriate to each modality (integration, clustering, annotation, differential expression).
• Analyze large-scale single-cell and spatial transcriptomics data, from raw output through to biological interpretation, including visualization of spatial data.
• Partner with wet-lab scientists to bring novel multi-omic assays online, developing the analysis methods and pipelines that new experimental modalities require.
• Collaborate with wet-lab and computational scientists to design experiments and interpret results.
• Provide technical guidance and mentorship across the bioinformatics, ML, and engineering teams, including code and method reviews.

Qualifications

• PhD in Bioinformatics, Genomics, Computational Biology, Computer Science, or a related field.
• 3+ years of experience developing, adapting, and benchmarking bioinformatics methods and building reproducible pipelines for large-scale single-cell and/or spatial transcriptomic data.
• Hands-on experience with single-cell transcriptomics analysis.
• Strong Python and/or R programming skills.
• Experience building reproducible workflows with a pipeline manager (e.g. Nextflow or Snakemake), containers, and version control.
• Experience applying state-of-the-art large language models (LLMs) to bioinformatics projects.
• Excellent organizational and documentation habits.

About You

• Experience with spatial transcriptomics data analysis and visualization.
• Experience applying and improving automated cell type annotation methods (e.g. marker-based and reference-based methods).
• Experience working at the interface of technology development and data analysis, particularly involving novel molecular biology or sequencing techniques.
• Strong domain knowledge in developmental biology or stem cell research.
• Experience mentoring scientists or reviewing scientific code.
• Prior experience in a startup or fast-paced, interdisciplinary environment.