Director of Computational Biology, Assay Cancer Research

Director of Computational Biology, Assay Cancer Research

As a Director of Computational Biology, Assay Research at Freenome, you will be a leader in the development of early, noninvasive tests for cancer detection. You will leverage a deep understanding of cancer biology and statistical/machine learning methods in order to guide a team of computational biologists working to discover the next generation of molecular assays and to open up early detection opportunities in new cancer indications. You will partner with wet lab experts in Molecular Research to plan studies, then support your team's analysis and interpretation of experimental data. You will provide scientific inspiration and strong technical guidance to team members, helping them to grow and develop as independent scientists, and empowering them to do their best work. Finally, you will be a key member of Freenome's scientific leadership team, contributing to decision making and selection of the directions we prioritize for research and development.

How you'll contribute:

• Lead a team engaged in research projects to measure and model biological changes resulting from cancer and precancerous lesions.
• Identify opportunities for new assay development and for new biomarker target identification and assessment. Partner closely with Molecular Research to plan the studies required for assessing assay and target hypotheses.
• Support the development of computational analysis methods for existing and novel multiomic assay data types at the forefront of research developments in cancer biology and biomarker discovery.
• Support the career growth and development of talented computational scientists. Mentor existing staff and recruit new staff with skill sets and scientific development goals aligned with Freenome's needs and mission. Guide them as they undertake independent work and shape their own scientific and professional directions.
• Serve as a key thought leader on Science leadership teams. Inspire a culture of scientific innovation, translating discoveries into high-impact clinical applications.
• Partner with other scientific staff at Freenome to develop a scientific roadmap and research strategy to turn discoveries into clinical diagnostics.
• Model "servant leadership" by supporting direct reports on projects large and small. Demonstrate a commitment to cultivating a holistic understanding of Freenome's research platform and organization structure in order to maximize the team's potential.

What you'll bring:

• PhD or equivalent experience in a relevant quantitative field such as computational biology, cancer biology, statistics, bioinformatics, or equivalent.
• 7+ years post-PhD experience applying computational techniques for biological discovery and/or product development. Record of high-quality achievements demonstrated by peer-reviewed publications, patents, or launched products.
• 3+ years of experience managing computational scientists, with a demonstrated ability to provide junior scientists with effective technical mentorship.
• Extensive knowledge of molecular biology, with experience leveraging this knowledge for problems in cancer biology, therapeutics, and/or diagnostics research.
• Deep experience in analyzing several of the following biological data modalities: genomics, epigenomics (e.g., Hi-C, ATAC-seq, bisulfite sequencing), proteomics (e.g., mass spectrometry, multiplexed immunodetection assays), transcriptomics (e.g., coding and non-coding RNA-seq), and peripheral immune cell and antibody repertoire characterization.
• To enable effective guidance of team members, evidence in past work of outstanding computational and statistical analysis, data visualization and programming skills (including deep experience with Python, R, or equivalent).
• Track record of selflessly supporting and growing highly effective cross-functional teams.
• Demonstrated ability to partner with laboratory scientists to design and support execution of experimental work.
• Demonstrated ability to translate scientific roadmaps into biological discoveries and/or clinical products.

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 audacious 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 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 alignment with those of the company. They embrace our values of empathy, integrity, striving for greatness, servant leadership, trust, and holding 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 others' good intentions, and being secure in knowing 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.

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