Senior Computational Biologist - Early Discovery Oncology
Recursion
August 22, 2026
Remote friendly (Salt Lake City, UT)
United States
Clinical Research and Development
In This Role, You Will
- Drive target discovery by evaluating molecular evidence for target nomination and validation, leveraging Recursion’s platform to identify novel precision oncology vulnerabilities.
- Pilot novel methods for target discovery, validation, and early patient population hypotheses to advance programs into nomination cascades.
- Define internal criteria for target data packages and early patient population strategy.
- Partner with platform and engineering teams to connect analysis methods to solutions and accelerate future work.
- Collaborate cross-functionally with biologists, medicinal chemists, translational, and portfolio leads to build data packages driving program milestones and investment decisions.
- Present data analysis to decision makers and stakeholders clearly and persuasively.
The Experience You’ll Need
- PhD in a relevant field (computational biology, bioinformatics, systems biology, cancer biology, etc.) with strong computational focus and 3+ years in biotech/pharma early drug discovery OR MS with 5+ years.
- Domain expertise in precision oncology and target identification.
- Strong understanding of patient genetics and pathway druggability.
- Experience applying probabilistic/statistical/ML methods to integrate complex biological and/or human clinical data using Python or R.
- Exceptional data visualization skills.
- Excellent cross-functional communication skills.
Nice to Have
- Experience building a target discovery engine using public/proprietary datasets.
- Experience with CRISPR or small-molecule perturbation screens for hypothesis validation.
- Exposure to advancing programs from proof of concept to IND.
Working Location
- Hybrid role; Salt Lake City, UT or New York, NY; in-office at least 50%.
- Drive target discovery by evaluating molecular evidence for target nomination and validation, leveraging Recursion’s platform to identify novel precision oncology vulnerabilities.
- Pilot novel methods for target discovery, validation, and early patient population hypotheses to advance programs into nomination cascades.
- Define internal criteria for target data packages and early patient population strategy.
- Partner with platform and engineering teams to connect analysis methods to solutions and accelerate future work.
- Collaborate cross-functionally with biologists, medicinal chemists, translational, and portfolio leads to build data packages driving program milestones and investment decisions.
- Present data analysis to decision makers and stakeholders clearly and persuasively.
The Experience You’ll Need
- PhD in a relevant field (computational biology, bioinformatics, systems biology, cancer biology, etc.) with strong computational focus and 3+ years in biotech/pharma early drug discovery OR MS with 5+ years.
- Domain expertise in precision oncology and target identification.
- Strong understanding of patient genetics and pathway druggability.
- Experience applying probabilistic/statistical/ML methods to integrate complex biological and/or human clinical data using Python or R.
- Exceptional data visualization skills.
- Excellent cross-functional communication skills.
Nice to Have
- Experience building a target discovery engine using public/proprietary datasets.
- Experience with CRISPR or small-molecule perturbation screens for hypothesis validation.
- Exposure to advancing programs from proof of concept to IND.
Working Location
- Hybrid role; Salt Lake City, UT or New York, NY; in-office at least 50%.