Computational Biologist

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.

• →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.
  

• 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.
  

• 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.