AIRx Director, Computational & AI Biologics Design Lead

Role: Serve as the strategic computational leader for Takeda's AI-driven biologics discovery within the AIRx initiative, focusing on in silico biologics design for large-molecule programs such as antibodies and multispecific formats. Responsibilities include developing and executing computational design strategies, utilizing generative AI and structure-informed methods to guide candidate selection, optimize lead development, and inform program decisions. The role involves close collaboration with biology, protein engineering, and translational teams, translating computational insights into actionable engineering priorities, and integrating structural biology data into design workflows. It also encompasses interfacing with Takeda’s AI/ML platform, defining data requirements, and shaping AI/ML model training datasets to accelerate discovery cycles. External engagement, scientific mentorship, and staying current with AI advancements in biologics are critical components. Qualifications include a PhD in Computational Biology, Structural Biology, Bioinformatics, or related fields, with 10+ years industry experience in biologics drug discovery, expertise in antibody/protein modeling, and proficiency in Python and ML deployment. Preferred skills include multispecific antibody experience, physics-based modeling integration, and prior involvement in IND-enabling programs. The position is based in Cambridge, MA, with a hybrid work arrangement. High-value biopharma specifics involve biologics design, AI/ML platform development, and biologics development stages, emphasizing innovation in large molecule modalities.