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Staff Computational Biologist
| Company | Freenome |
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| Location | Daly City, CA, USA |
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| Salary | $161925 – $247000 |
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| Type | Full-Time |
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| Degrees | Master’s, PhD |
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| Experience Level | Senior |
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Requirements
- Post-graduate degree (MS or PhD) in statistics, computational biology, bioinformatics, cancer biology, or related quantitative field
- 3+ years of industry experience
- Experience with molecular biology
- Experience in experimental design and analysis of high-throughput, quantitative technologies
- Familiarity with and ability to select and leverage bioinformatics tools for the above molecular assays
- Experience in applied statistics, such as in hypothesis testing, GLM, and appropriate use of simulation
- Expertise in data analysis and visualization using R (tidyverse), or Python statistical packages (Numpy, Matplotlib, Pandas), or equivalent, under version control
- Excellent oral and written communication skills to communicate to scientific and broader audiences, with keen attention to detail
- Ability to work on a cross-functional team in our highly collaborative environment, working with both computational and experimental scientists
Responsibilities
- Plan and execute development experiments for Freenome’s multiomics cancer screening tests
- Partner cross-functionally with computational, development, regulatory, and quality leaders to develop and execute a regulated development strategy working toward FDA approval
- Use your quantitative skills to develop computational methods and interpret complex experimental results in order to optimize and validate innovative technology for sample collection, preparation, and detection
- Develop and execute appropriate experimental design and analysis plans for Development, Verification, and Validation studies, closely partnering with Biostatistics, Development, and Pre-Analytics teams
- Work closely with molecular and computational research teams developing Freenome’s IVD products for blood-based molecular assays involving cell-free DNA
- Impact patient lives through the development and launch of high quality cancer screening technologies
Preferred Qualifications
- Experience in the development of diagnostic devices in a regulated environment (PMA, 510(k), CE-IVD) preferred
- Experience with different NGS methods (e.g. target capture with UMI, Hi-C, ATAC-seq, RNA-seq, bisulfite sequencing, microarrays)
