Principal Scientist, Computational Protein Design

Flagship Pioneering, Inc. • Cambridge, MA

102d

About The Position

Pioneering Intelligence is a strategic initiative of Flagship Pioneering committed to positioning Flagship at the forefront of global prosperity through the synthesis of human, machine, and nature’s intelligence -- which we call Polyintelligence. Pioneering Intelligence is seeking a Principal Scientist – Computational Protein Design to serve as the technical lead on computational antibody design efforts pushing the forefront of AI-based antibody design approaches on high value targets. This position will be in collaboration with Pioneering Medicines, Flagship Pioneering’s initiative building a world-class biopharmaceutical R&D capability harnessing the power of Flagship’s scientific platforms. As Principal Scientist – Computational Protein Design, you will lead technical development in computational antibody design and developability optimization, playing a pivotal role in advancing our AI-based design methods to build new foundational workflows for end-to-end antibody design, and apply those workflows to advance new medicines in collaboration with Pioneering Medicines. The ideal candidate will combine strong scientific and computational know-how with proficiency in working within highly matrixed, cross-functional team environments. Join us to shape the future of cutting-edge antibody therapeutics across Flagship’s portfolio of technology platforms.

Requirements

• PhD in Biochemistry, Structural Biology, Biophysics, Protein Engineering, Computational Biology, Computer Science, or related field with 5+ years of relevant industry experience.
• Proven experience in the end-to-end design and optimization of antibodies for binding, functionality, and developability.
• Strong track record in utilizing AI and computational methods for antibody engineering, including but not limited to AI-based co-folding models and design models, and related structure-based design tools.
• Experience analyzing and interpreting antibody developability data.
• Experience leading projects in antibody discovery or biologics development.

Nice To Haves

• Expertise in a breadth of antibody modalities, including mAbs, bispecifics or multispecifics, antibody-drug conjugates (ADCs), and antibody fragments.
• Experience developing and training novel AI and machine learning models for protein engineering utilizing deep learning architectures.

Responsibilities

• Design and optimize antibodies using AI-based and structure-based approaches for binding and functionality.
• Create and apply computational methods for assessing and optimizing developability (stability, solubility, manufacturability, immunogenicity, polyreactivity, polyspecificity).
• Improve AI models with experimentally generated data.
• Stay at the forefront of AI and computational tools in antibody engineering.
• Provide scientific leadership and mentor team members.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree
• Number of Employees: 251-500 employees