About Cartography Biosciences

Cartography Biosciences is a therapeutics organization creating the first atlas to identify targets that are specific enough to only engage cancerous cells, broad enough to work across cancer cells and patients, and safe enough to sidestep toxic side effects. Founded by Kevin Parker, Howard Chang, and Ansu Satpathy, Cartography is bridging immunology and computation to understand the critical differences between normal and cancerous cells, ultimately solving the challenge of finding the safest, most selective targets for a variety of immunotherapeutic approaches. 

We are looking for a Computational Biologist to help create analytical methods and software tools that aid our target identification and translational research efforts. You will work with single-cell multi-omics analysis, internal platform development, and data visualization to support our expanding pipeline.

This role combines bioinformatics development, software engineering, and translational science. You will prototype and improve computational approaches, build maintainable software packages, and present analytical findings as engaging data stories for both scientific and investor audiences. The candidate will primarily work as an individual contributor, with input from colleagues in Computational Sciences, Research and Discovery, and DevOps.

Key Responsibilities

• Prototype and improve computational methods for analyzing single-cell multi-omics data (e.g., scRNA-seq, CITE-seq, scATAC-seq), working with DevOps and engineering team members to turn validated methods into scalable production pipelines.
• Develop and implement computational methods for analyzing phage and yeast display panning and enrichment data, including next-generation sequencing readouts of binder selection campaigns.
• Build and maintain internal bioinformatics software packages and pipelines, using a shared codebase and following version control best practices.
• Turn complex analytical results into clear, publication-quality figures and data narratives for scientific and investor audiences.
• Collaborate with wet-lab scientists to design experiments, troubleshoot data quality, and interpret results from new assays, including phage/yeast display and antibody characterization workflows.

Required Qualifications

• PhD in Bioinformatics, Computational Biology, Computer Science, or a related field; or MS with 3+ years of relevant experience; or BS with 4+ years of relevant experience.
• Hands-on experience with single-cell multi-omics analysis, particularly with scRNA-seq.
• Proven experience building and maintaining a bioinformatics software package or analysis framework.
• Strong skills in Python and familiarity with the Unix/bash command line.
• Comfortable using Git/GitHub in a collaborative codebase.
• General understanding of immunology, cancer biology, and antibody discovery platforms.

Preferred Qualifications

• Experience with additional single-cell techniques such as CITE-seq, multi-ome, or spatial transcriptomics.
• Experience with BEAM (Barcode Enabled Antigen Mapping) or similar B-cell antigen specificity profiling methods.
• Experience in computational analysis of phage or yeast display panning and enrichment campaigns.
• Familiarity with R.
• Knowledge of transformer-based or foundation model methods for single-cell biology (e.g., scGPT, Geneformer).
• Experience with cloud computing platforms, preferably GCP.