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Strong employer brand and metro location, but niche computational biology ML reduces applicant density.
Highly specialized computational biology and clinical trial expertise limits cross-industry transferability.
Requires senior biotech ML expertise, PhD/Master plus production ML and multi-omic experience, strict filters.
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Design and implement predictive and prognostic biomarker models from clinical trial and biomarker data focusing on disease stratification, efficacy, safety, and adverse event outcomes.
Develop multi-omic data integration frameworks and advanced statistical models for translational insights across drug development programs.
Build, evaluate, and contribute to AI and machine learning systems including foundation models, generative models, and agentic AI to support analysis and decision-making in regulated environments.
Doctorate in Bioinformatics, Computational Biology, Statistics, Mathematics, Computer Science, Data Science, or related quantitative field with 8+ years relevant experience OR Master’s degree with 3-5 years relevant experience including 2-3 years in industry.
Proven expertise in Python and R for scientific computing and modeling.
Experience with clinical trial data, biomarker strategies, and multi-omic datasets integration.
Work Experience Required: Minimum 8 years post-PhD or 3-5 years with Master’s including 2-3 years industry experience.
Deep expertise in quantitative modeling and computational biology demonstrated by peer-reviewed publications, production-grade code, or verifiable industry impact.
Experience working in global biotech or pharmaceutical environments with complex, interdisciplinary data and teams.
Proven ability to own end-to-end analytical projects that influenced scientific or development decisions, balancing sophisticated methods with clinical relevance.