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

Calliere Group
Posted 4 months ago, valid for 25 days
Location

Fremont, Alameda 94536, CA

Salary

Competitive

Contract type

Full Time

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Sonic Summary

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  • Join a team focused on developing data-driven diagnostics at the intersection of biology, computation, and machine learning.
  • The role requires a Ph.D. or equivalent experience in computational biology, bioinformatics, or a related quantitative field, along with 5+ years of hands-on experience with sequencing data.
  • Key responsibilities include architecting computational pipelines, applying statistical frameworks, and collaborating with biologists and engineers to innovate diagnostics.
  • Candidates should have a strong engineering mindset, proficiency in Linux, and a deep understanding of algorithmic performance and statistical rigor.
  • The position offers a competitive salary, reflecting the expertise and impact of the role in transforming patient outcomes.

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.

What You’ll Do

  • Architect and optimize computational pipelines that turn raw high‑resolution molecular data into clean, interpretable insights.

  • Apply advanced statistical and algorithmic frameworks to analyze ultra‑large cell‑level and spatial datasets.

  • Design and validate novel biomarkers and molecular signatures that accelerate diagnostic innovation.

  • Maintain scalable, reproducible data workflows capable of handling cohorts of hundreds or thousands of biological samples.

  • Partner with biologists, data scientists, and software engineers to push new ideas from concept to clinical utility.



Requirements

What You Bring

  • Ph.D. (or equivalent experience) in computational biology, bioinformatics, genomics, or a quantitative discipline.

  • 5+ years working hands‑on with single‑cell, spatial, or high‑throughput sequencing data.

  • Deep understanding of algorithmic performance, statistical rigor, and how analytical assumptions translate to biological meaning.

  • Strong engineering mindset — you write clean, extensible code that scales gracefully.

  • Expert‑level fluency in Linux and modern programming ecosystems.

  • Independent drive, intellectual curiosity, and relentless attention to detail.

Bonus Points For

  • Experience with next‑generation spatial or single‑cell assay platforms.

  • Background in oncology, immunology, or systems‑level disease research.

  • Familiarity with biomarker discovery pipelines or clinical data integration.

  • Machine learning or statistical modeling applied to multi‑omic data.

  • Practical experience with workflow orchestration (Nextflow, Snakemake, or similar).

  • Solid software engineering habits — reproducible analysis, version control, peer review, and testing.

  • Comfort operating in high‑performance or cloud computing environments.

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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