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Freenome
Staff Computational Biologist
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What they do
A Computational Biologist uses biological data to develop models to better understand biological systems. Conducts analysis using computational and mathematical methods and large data sets.
$137,317 / year median in California
+8% projected growth
Job Description
Staff Computational Biologist Freenome - 3.0 Brisbane, CA Job Details $188,275 - $270,375 a year 4 hours ago Qualifications Computational research Assay development Programming languages Collaboration with product development teams Doctor of Philosophy Oncology research Developing data pipelines Clinical data analysis Bioinformatics data analysis Cross-functional communication Data analysis software Developing new products Full Job Description About this opportunity: At Freenome, we are seeking a Staff Computational Biologist to help grow the Freenome Computational Biology, Assay Research (CBAR) team. As part of our team, you will apply your scientific expertise to the development of early, noninvasive tests for cancer detection. With a strong background in NGS assay development, bioinformatics, statistics, and molecular biology, you will design and execute research studies to drive early research of prototype cancer early detection products using cfDNA as biomarker. You will work closely and cross-functionally with many teams, including Molecular Research and Development, Model R D, and Computational Biology, Assay Development to enable the concept and feasibility of multiple molecular assays as part of Freenome's diagnostic products. The role reports to a Manager and Senior Staff Computational Biologist. This position can be a hybrid or fully remote role. What you'll do: Lead the analysis and interpretation of molecular and clinical data in the context of early cancer detection, serving as a key thought leader on the Computational Science team. Suggest research hypotheses and areas for potential computational model and assay improvement; then plan, scope, and execute associated research in partnership with a multidisciplinary team, owning projects from ideation through implementation. Develop bioinformatics pipelines to enable high throughput NGS data processing and analysis. In collaboration with wet lab scientists, rapidly characterize and iterate on experimental methods by providing real-time assessments of assay performance, quality control, and clinical/diagnostic utility. Remain at the forefront of molecular techniques in oncology, and collaborate with the larger team to bring forward the next generation of assays for early cancer detection.