Assay Characterization & Validation
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Execute data analyses supporting assay characterization across multiple epigenomic and NGS-based diagnostic tests — from raw data processing through performance metric generation
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Design and implement quality assessment frameworks to evaluate assay and pipeline performance, including QC metric definition, threshold setting, and failure mode identification
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Run and interpret validation experiments in close coordination with wet lab and senior computational team members, contributing to study execution against pre-defined protocols
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Pursue defined research questions semi-independently — taking a scoped problem, designing the analytical approach, executing, and returning well-documented results
In Silico Simulation & Thresholding
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Design and run in silico simulations to model assay behavior under variable conditions — including signal dropout, coverage non-uniformity, and input DNA variability
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Develop and apply statistical approaches to threshold setting and performance boundary definition, supporting limit of detection and analytical range characterization
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Systematically explore parameter sensitivity across bioinformatics pipelines to assess model robustness and inform feature selection
Regulatory Support & Communication
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Produce clear, thorough documentation of all analyses code, methods, results, and interpretation to the standard required under design controls
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Contribute to the authoring of SOPs and analytical summary reports
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Partner closely with wet lab scientists to ensure computational analyses are grounded in experimental reality and that results are communicated in accessible, actionable terms
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Present analytical findings clearly in team meetings and cross-functional settings
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Contribute to a collaborative team environment by sharing code and knowledge openly and proactively
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MSc in computational biology, bioinformatics, biostatistics, or a closely related quantitative field with 3–4 years of industry or post-graduate research experience in a data-intensive biological or biomedical setting, Ph.D. preferred
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Strong proficiency in R and Python for data analysis, visualization, and reproducible reporting — you write, own, and document your own code
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Experience with cloud computing environments (AWS) for running scalable analyses
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Demonstrated ability to execute analytical plans with precision and efficiency, managing multiple tasks without a drop in quality or documentation standards
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Familiarity with NGS data types and standard processing pipelines — alignment, QC, coverage analysis, or equivalent
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Clear and organized communicator — written documentation, results presentations, and cross-functional interactions alike
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Comfortable working in a fast-paced startup environment, following defined protocols while contributing ideas for improvement
Nice to have:
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Exposure to regulated environments — CLIA, CAP, FDA IVD, or design controls in any form
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Experience with epigenomic data types — methylation, cfDNA, chromatin accessibility, or ChIP-seq
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Familiarity with statistical thresholding or limit of detection frameworks for diagnostic applications
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Experience contributing to SOPs, validation reports, or other regulated documentation
Associate Scientist: $110,000 - $130,000
Scientist I: $125,000 - $145,000
Final compensation will be based on a candidate’s qualifications, experience, and geographic location. Employees are also eligible for performance bonuses, equity participation and comprehensive health benefits.