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Strong employer brand and metro location but highly specialized AI+biomedical skillset reduces applicant density.
Highly domain-specific scientific and translational expertise reduces cross-industry transferability.
Requires deep biomedical and AI expertise, PhD-level qualifications, and leadership, enforcing strict candidate filters.
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Lead development and execution of AI strategies to accelerate disease biology research, target identification, and translational science workflows.
Design and implement AI-driven intelligent workflows integrating knowledge graphs, literature, and computational models to enhance scientific reasoning and discovery productivity.
Serve as primary scientific leader interfacing with disease scientists and AI/ML engineers to ensure AI outputs remain biologically meaningful and actionable.
PhD in Biology, Computational Biology, Bioinformatics, Biomedical Informatics, Systems Biology, Computer Science, or related field.
Experience applying AI, machine learning, or knowledge-driven systems to biological research.
Demonstrated leadership in cross-functional scientific programs.
Work Experience Required: Not explicitly mentioned in the JD.
Deep expertise in disease biology, translational science, or computational biology combined with strong knowledge of AI technologies like knowledge graphs and foundation models.
Strategic thinker able to translate scientific challenges into AI opportunities and guide complex multi-agent, knowledge-driven workflows.
Experience working cross-functionally with scientists, ML engineers, and platform teams to embed AI in therapeutic research programs.