Senior Computational Scientist – Systems Biology & Next‑Gen Data Engineering

Step into a role where code meets clinical impact. We’re building the next generation of data‑driven diagnostics — at the intersection of biology, computation, and machine learning. You’ll join a tight\-knit team of scientists and engineers decoding huge multi‑omic datasets to uncover patterns that actually change patient outcomes.
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What You’ll Do
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• Architect and optimize computational pipelines that turn raw high‑resolution molecular data into clean, interpretable insights.
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• Apply advanced statistical and algorithmic frameworks to analyze ultra‑large cell‑level and spatial datasets.
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• Design and validate novel biomarkers and molecular signatures that accelerate diagnostic innovation.
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• Maintain scalable, reproducible data workflows capable of handling cohorts of hundreds or thousands of biological samples.
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• Partner with biologists, data scientists, and software engineers to push new ideas from concept to clinical utility.
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  Requirements<\/h3>

  What You Bring
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  • Ph.D. (or equivalent experience) in computational biology, bioinformatics, genomics, or a quantitative discipline.
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  • 5+ years working hands‑on with single‑cell, spatial, or high‑throughput sequencing data.
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  • Deep understanding of algorithmic performance, statistical rigor, and how analytical assumptions translate to biological meaning.
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  • Strong engineering mindset — you write clean, extensible code that scales gracefully.
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  • Expert‑level fluency in Linux and modern programming ecosystems.
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  • Independent drive, intellectual curiosity, and relentless attention to detail.
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    Bonus Points For
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    • Experience with next‑generation spatial or single‑cell assay platforms.
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    • Background in oncology, immunology, or systems‑level disease research.
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    • Familiarity with biomarker discovery pipelines or clinical data integration.
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    • Machine learning or statistical modeling applied to multi‑omic data.
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    • Practical experience with workflow orchestration (Nextflow, Snakemake, or similar).
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    • Solid software engineering habits — reproducible analysis, version control, peer review, and testing.
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    • Comfort operating in high‑performance or cloud computing environments.
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      If you’re driven by the idea of building tools that help decode biology at scale and you thrive where data meets diagnostics, this is your stage.
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