Staff Computational Biologist - Cancer Biology

As a Staff Computational Biologist focused on Cancer Biology at Freenome, you will be a key scientific leader in the development of early, noninvasive tests for cancer detection. As a senior member of the team, you will use a strong foundation of the biological mechanisms of cancer to motivate hypotheses, develop, and make improvements to computational algorithms detecting molecular signatures of cancer. You will work closely with and lead the work of machine learning scientists, molecular biologists, and other computational biologists on a collaborative team to drive the iteration of computational models and assays while ultimately developing products which can be used in the clinic.

How you’ll contribute:

• 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.
• Motivate research hypotheses and areas for potential model improvement, and subsequently plan, scope, and execute associated research with a talented team of computational biologists.
• Leverage, develop, and apply machine-learning and statistical tools for models development and interpretation .
• Remain at the forefront of research developments in cancer biology, including but not limited to early cancer detection and molecular signatures across various types and stages of cancer.
• Use foundational knowledge in cancer biology to analyze and interpret data from best in class molecular assays such as whole genome sequencing, whole genome bisulfite sequencing, targeted sequencing, RNA sequencing, and protein quantitation.
• Work closely with molecular biologists to collaboratively iterate on experiments in the wet lab.

What you’ll bring: 

• PhD or equivalent experience in a relevant field such as biology, cancer biology, computational biology, computer science, and other quantitative fields.
• 5+ years post-PhD experience applying computational techniques for biological discovery and product development, ideally in industry. 
• Experience in developing, applying, and evaluating statistical and/or machine learning algorithms.
• Extensive knowledge of cancer biology and molecular biology, with experience leveraging this knowledge for problems in cancer computational biology and diagnostics.
• Experience with computational and statistical programming, including experience with Python statistical and machine-learning packages. Equivalents in other languages like R are also suitable.
• Strong quantitative reasoning and statistical analysis skills, with a demonstrated ability to apply them effectively to relevant scientific problems.
• Experience in the analysis of high-throughput, quantitative technologies in genomics, epigenomics, proteomics, or transcriptomics (e.g. Hi-C, ATAC-seq, RNA-seq, MS).
• Expertise with biological and genomic data, tools, and associated public databases (e.g. ENCODE, TCGA, Blueprint, Cosmic).
• Excellent oral and written communication skills to communicate to both scientific and broader audiences.
• Experience mentoring or managing junior scientists, with an ability to work on a cross-functional team (with both computational and experimental scientists).

Freenome has adopted a COVID-19 vaccination policy to safeguard the health and well-being of our employees. As a condition of employment, our employees working on-site are required to be fully vaccinated for COVID-19, unless a reasonable accommodation is approved or as otherwise required by law.

About Freenome

Freenome is on a mission to empower everyone with the tools they need to detect, treat, and ultimately prevent cancer.

We have pioneered the most comprehensive multiomics platform for early cancer detection through a routine blood draw.  By combining deep expertise in molecular biology with advanced computational biology and machine learning techniques to recognize disease-associated patterns among billions of circulating, cell-free biomarkers, we are developing simple and accurate blood tests for early cancer detection and integrating the actionable insights into health systems to operationalize a machine learning feedback loop between care and science. 

Our recent $270 Million Series C brings our financing to over $500 million from investors, including;  Bain Capital, Perceptive Advisors, RA Capital, Polaris Partners, Andreessen Horowitz, funds and accounts advised by T. Rowe Price Associates, Inc., GV (formerly Google Ventures), Roche Venture Fund, Kaiser Permanente Ventures, American Cancer Society’s BrightEdge Ventures, Data Collective Venture Capital, Novartis and Verily Life Sciences. 

Our Science

Freenome is building technology to advance the understanding of cancer through multiple analytes derived from blood. These signals include cell-free DNA, methylation of cell-free DNA, cell-free RNA, circulating proteins, and immune profiling derived from thousands of prospective samples. By developing novel statistical learning methods and applying them to integrate various -omics datasets, Freenome is a leader in modeling specific biological mechanisms to capture disease-dependent signatures including gene expression, immune response, tumor burden, the tissue of origin, and 3D chromatin structure. 

By building comprehensive discovery datasets and modeling critical biological systems, Freenome is learning what biological changes are present within the blood between a variety of different disease states including cancer, autoimmune disorders, infections, drug response, and aging. The synthesis of Freenome’s datasets, cross-functional technical expertise, and intrepid mission to discover biological truth, we seek to improve the lives of millions through early detection and early treatment of disease.  

Our Culture

Freenomers are technical, creative, visionary, grounded, empathetic, and passionate. We build teams around divergent expertise, allowing us to solve problems and ascertain opportunities in unique ways. Freenomers are some of the most talented experts in their fields, joining together to advance healthcare, one breakthrough at a time. 

We value empathy, integrity, and trust in one another and we respect the diverse perspectives of our colleagues and of those we serve.  We assume positive intent and give each other the benefit of the doubt with the firm belief that we are a team working toward the same objectives.  We believe in empowering and supporting each other in a collaborative and dynamic environment. 

What does a successful person look like at Freenome?

Those who thrive at Freenome prioritize, manage, and execute their own goals with ownership and in alignment with those of the company. They embrace our values of empathy, integrity, striving for greatness, servant leadership, and trust, and hold themselves and their team accountable to these values. They crave collaboration with brilliant minds from disparate fields of study and believe that hiring and mentorship are fundamental to our success. Above all, they welcome and provide constructive feedback and criticism, trusting in the good intentions of others, and being secure in the knowledge that embracing mistakes is the best way to learn and grow. For those who pursue challenges, understudied problems, and want the opportunity to see their work impact the lives of millions of people affected by cancer every year, there’s no better place to be than Freenome.

Freenome is proud to be an equal opportunity employer and we value diversity. Freenome does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status, or any other basis covered by appropriate law.