Success in this role will require scientific independence, sound judgment, and effective collaboration across disease biology, experimental genomics, translational research, computational sciences, and project leadership.  

This position is based in San Diego, CA and is eligible for on‑site or hybrid work, with an expectation of at least three days per week on‑site. 

Key responsibilities: 

• Partner closely with cross-functional project teams to identify critical scientific questions that can be addressed through human genetics, genomics, sequencing, and computational analyses.

• Design, execute, and interpret human genetic, genomic, and multi-omic studies that advance target discovery, target validation, biomarker development, and mechanistic understanding. 

• Apply and develop computational and statistical approaches to analyze complex biological datasets, integrating internal data with publicly available resources to generate actionable insights. 

• Take ownership of analyses from biological question through recommendation, clearly communicating conclusions, limitations, and proposed next steps to diverse scientific audiences. 

• Help shape genomics strategies across discovery programs, ensuring that study design, analysis plans, and interpretation are scientifically rigorous and aligned with project objectives. 

• Collaborate with computational and experimental scientists to identify opportunities where emerging computational approaches, including machine learning and AI technologies, can accelerate biological discovery and enhance the analysis and interpretation of genomic and human genetic data. 

• Contribute to scientific publications, internal reports, regulatory submissions, and other communications that support research and development activities. 

Knowledge and Skills: 

• Deep understanding of human genetics, genomics, and their application to disease biology, target discovery, and therapeutic development.

• Strong scientific judgment and the ability to translate complex datasets into clear conclusions, recommendations, and next steps.

• Ability to independently drive scientific questions from study design through interpretation and influence project decision-making.

• Excellent communication skills, including the ability to convey complex scientific concepts to diverse audiences.

• Interest in evaluating and applying emerging computational approaches, including machine learning and AI technologies, where they can meaningfully advance biological discovery.

• A team-oriented growth mindset that welcomes feedback from others and supports other team members; a positive attitude that enthusiastically tackles and overcomes challenges

Minimum Qualifications: 

• PhD in computational biology, bioinformatics, genomics, human genetics, systems biology, bioengineering, or a related field, with 3+ years of relevant post-doctoral or industry experience; or Master's degree in a related field with 8+ years of relevant industry experience. 

• Demonstrated excellence in the analysis, visualization, and interpretation of human genetics, genomic, and next-generation sequencing (NGS) data. 

• Experience applying computational methods and bioinformatics tools to large-scale biological datasets. 

• Proficiency in programming (R, Python), Unix/Linux environments, and high-performance computing systems. 

• Solid foundation in statistics and genetics, including the role of human genetic variation in disease biology.