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Computational Biologist

$131.33k - $189.53k

Freenome

At Freenome, we are seeking a 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 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. 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. Must haves: PhD degree in computational biology, cancer biology, statistics, bioinformatics, or related quantitative field. Experience in NGS assay and pipeline development. Demonstrated track record of implementing complex workflows for high throughput NGS data processing. Strong quantitative reasoning and data analysis skills, with a demonstrated ability to apply them effectively to relevant scientific problems. Strong computational and programming skills, including thorough experience with Python statistical packages (Numpy, Matplotlib, Pandas) or equivalents in other languages like R. Excellent oral and written communication skills to communicate to both scientific and broader audiences. Ability to work on a cross-functional team in our highly collaborative environment, working with both computational and experimental scientists. Nice to haves: Expert knowledge of chromatin biology, liquid biopsy, DNA methylation and their relevance in cancer early detection. Extensive experience working with DNA methylation data for biomarker discovery research. Experience in developing, applying, and evaluating statistical and/or machine learning algorithms. Benefits and additional information: The US target range of our base salary rate for new hires is $131,325 - $189,525. You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered. Please note that individual total compensation for this position will be determined at the Company’s sole discretion and may vary based on several factors, including but not limited to, location, skill level, years and depth of relevant experience, and education. Freenome is proud to be an equal-opportunity employer, and we value diversity. Freenome does not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law. Applicants have rights under Federal Employment Laws. California applicants please review the CCPA Notice at Collection here. #J-18808-Ljbffr Freenome

Vacancy posted 1 day ago
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