About the role
As a Director of Computational Biology, Assay R&D at Freenome, you will be a leader contributing to the development of noninvasive tests for early cancer detection. You will lead a team of talented computational biologists & statistical scientists working closely with wet-lab scientists in Freenomes Molecular Research & Assay Development groups to drive the conception, design, optimization, & development of high-throughput assays for cell-free nucleic acids, circulating proteins, & other biomarkers in the blood. This highly collaborative work will produce the assays that are integrated into Freenomes multiomics biomarker discovery platform & commercial tests for early cancer detection. You will partner with leadership & scientific staff in the Molecular Research & Assay Development departments to plan studies, then support your teams analysis & interpretation of experimental data. You will leverage a deep understanding of computational approaches to cancer genetics, epigenetics, & molecular biology to provide scientific inspiration & technical guidance to team members, helping them to grow & develop as independent scientists, & empowering them to do their best work. Finally, you will be a key member of Freenomes scientific leadership team, contributing to decision making & prioritization of our research & development directions.
How youll contribute
- Lead a team engaged in research & development projects to measure & model biomarkers associated with cancer & precancerous lesions. Team responsibilities include:
- Applying knowledge of computational biology to support the development of assays for high-throughput measurement of cell-free nucleic acids, circulating proteins, & other biomarkers in the blood.
- Understanding, constructively applying, & developing best-in-class computational tools to extract actionable information from high-throughput assay datasets.
- Collaborating with wet-lab scientists to rapidly iterate & to design or improve on existing experimental methods & quality control metrics, by providing real-time assessments of performance throughout the assay R&D process.
- Identifying, implementing, & characterizing the behavior of appropriate quality control metrics throughout the assay development process.
- Providing computational & statistical support to bench scientists throughout Freenomes Molecular Research & Assay Development teams.
- Collaborating with bioinformatics & machine learning pipeline engineers to scale & strengthen computational approaches from the R&D lab through to deployment as high-throughput reproducible workflows, & ultimately as components of the regulated, production-grade software used by Freenomes commercial blood tests.
- Serve as a key thought leader on the Computational Science & larger Science leadership teams. Partner with other scientific staff at Freenome to develop a scientific roadmap & research strategy.
- Nurture & grow a computational scientist team, by mentoring existing staff & by recruiting & hiring new staff with skill sets & scientific development goals aligned with Freenomes needs & mission. Create opportunities for your team members to undertake independent work & shape their own scientific & professional directions.
- Have a multiplicative effect by building & harmonizing data analysis infrastructure & best practices within the team, & aligning analysis & infrastructure practices with Freenomes larger Computational Science & Software Engineering communities when appropriate.
- Inspire a culture of scientific innovation, translating discoveries into high-impact clinical applications.
- Model servant leadership by maximizing the full teams potential for impactful contribution.
What youll bring
- PhD or equivalent experience in a relevant, quantitative field such as computational biology, statistics, bioinformatics, or equivalent. Alternately, a PhD in molecular or cancer biology (or similar) with extensive evidence of high-quality application & mastery of contemporary computational biology techniques (e.g., lead authorship on peer-reviewed publications).
- 7+ years post-PhD experience applying computational techniques to biological discovery and/or product development. Record of high-quality achievement demonstrated by peer-reviewed publications, patents, or successfully developed products.
- Industry experience working in a diagnostics, pharmaceutical, or other biotechnology environment. Experience with CLIA/NYS/FDA assay validation studies is a plus.
- 3+ years of demonstrated experience managing & mentoring computational scientists.
- Extensive knowledge of cancer molecular biology, with experience leveraging this knowledge for problems in therapeutic or diagnostic research & development.
- Outstanding command of statistics, quantitative data analysis, & complex data visualization, including deep experience with statistical packages in Python, R, or equivalent.
- Deep experience in analyzing several of the following biological data modalities: genomics, epigenomics, proteomics, transcriptomics (RNA-seq).
- Understanding of library preparation methods used to generate next-generation sequencing data, including whole-genome & targeted approaches, genetic & epigenetic DNA characterization, & RNA-seq.
- Track record of selflessly supporting & growing highly effective cross-functional teams, & of collaborating closely with bench scientists. Direct experience developing novel molecular biology assays, which could possibly include hands-on experience at the bench, is a plus.
Freenome is on a mission to empower everyone with the tools they need to detect, treat, & 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 & machine learning techniques to recognize disease-associated patterns among billions of circulating, cell-free biomarkers, we are developing simple & accurate blood tests for early cancer detection & integrating the actionable insights into health systems to operationalize a machine learning feedback loop between care & 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 & accounts advised by T. Rowe Price Associates, GV (formerly Google Ventures), Roche Venture Fund, Kaiser Permanente Ventures, American Cancer Societys BrightEdge Ventures, Data Collective Venture Capital, Novartis & Verily Life Sciences.
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, & immune profiling derived from thousands of prospective samples. By developing novel statistical learning methods & 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, & 3D chromatin structure.
By building comprehensive discovery datasets & 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, & aging. The synthesis of Freenomes datasets, cross-functional technical expertise, & audacious mission to discover biological truth, we seek to improve the lives of millions through early detection & early treatment of disease.
Freenomers are technical, creative, visionary, grounded, empathetic, & passionate. We build teams around divergent expertise, allowing us to solve problems & 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, & trust in one another, & we respect the diverse perspectives of our colleagues & those we serve. We assume positive intent & 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 & supporting each other in a collaborative & dynamic environment.
What does a successful person look like at Freenome?
Those who thrive at Freenome prioritize, manage, & execute their own goals with ownership & alignment with those of the company. They embrace our values of empathy, integrity, striving for greatness, servant leadership, trust, & holding themselves & their team accountable to these values. They crave collaboration with brilliant minds from disparate fields of study & believe that hiring & mentorship are fundamental to our success. Above all, they welcome & provide constructive feedback & criticism, trusting in others good intentions, & being secure in knowing that embracing mistakes is the best way to learn & grow. For those who pursue challenges, understudied problems, & want the opportunity to see their work impact the lives of millions of people affected by cancer every year, theres no better place to be than Freenome.
Freenome is proud to be an equal opportunity employer & 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.