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Bioinformatician (Spatial & Single-Cell) at Deep Science Ventures. StealthCo. is a seed-stage techbio company, created within DSV, building a computational drug discovery platform that constructs causal biological networks from large-scale primary human single-cell omics data and structured published experimental literature. Our multi-agent AI system reasons over these networks to generate, simulate, and rank mechanistic hypotheses for combination therapies — with system accuracy verified against top-tier researchers at the Allen Institute. We will initially focus on oncology indications.. The Role (remote, timezone-restricted). You will design and build production bioinformatics pipelines for new modalities—spatial transcriptomics, single-cell proteomics, and spatial proteomics—extending our existing scRNA-seq infrastructure. These pipelines feed directly into an agentic hypothesis generation system: the quality of what goes in determines the quality of every therapeutic hypothesis that comes out.. You’ll work closely with our Head of AI & Technology (Dr. Francesco Moramarco) and Head of Platform (Dr. Moustafa Khedr) to:. Build end-to-end pipelines (ingestion, QC, normalisation, integration, annotation, differential analysis). Design modality-specific statistics: spot deconvolution, spatial autocorrelation, ADT normalisation, protein-RNA joint embedding, segmentation, spillover correction. Extend hierarchical cell type annotation across modalities. Codify best-practice workflows into reusable templates for agent execution. Sanity-check outputs to catch batch effects and artefacts before they propagate. PhD in computational biology, bioinformatics, genomics, systems biology, or related quantitative field. 2–6 years experience in early-stage/high-growth startups. Pipeline-building experience with spatial transcriptomics (Visium, MERFISH, Xenium) from scratch. Experience with single-cell or spatial proteomics (CITE-seq, CyTOF, CODEX, IMC). Strong Python engineering in the anndata ecosystem (scanpy/squidpy/muon). Deep single-cell & spatial statistics knowledge (pseudobulk, multiple testing correction, mixed-effects models, compositional analysis). Strong biology grounding; can distinguish biology vs confound; assess mechanistic plausibility. Timezone: at least 5 hours overlap with UK working hours (UTC−4 through UTC+4 preferred). Strong desirables. Tumour biology / cancer immunology (TME, immune evasion, resistance). Comfort working in an AI-mediated workflow and writing analysis plans executed by agents. Experience building pipelines/tools consumed by others; cloud compute (GCP preferred); R proficiency. Nice to have. Wet lab experience and familiarity with the 10x Genomics ecosystem. We know job descriptions like this can read as a wish list. If you don't tick every box, but believe you can build what we need - apply anyway! We care more about what you've built and how you think than whether your CV maps perfectly to every bullet point.. Company Location: United Kingdom.