Senior Scientist, AI‑Enabled Structural Biology

Job Description & Responsibilities

Pfizer is seeking a Senior Scientist in AI-Enabled Structural Biology to advance structure-based discovery by integrating AI-guided protein design, structure prediction, and cryo-electron microscopy (cryo-EM), including AI/ML-enabled data analysis. This role is intended for a scientist who can apply and adapt state-of-the-art protein design methodologies to translate computational approaches into experimentally tractable solutions and leverage AI/ML approaches to accelerate structural discovery. In particular, the candidate will utilize de novo designed proteins, engineered constructs, scaffolds, and conformational stabilizers to expand structural access and mechanistic understanding of challenging targets for structure-based drug design (SBDD) across diverse modalities, including small molecules, biologics, and vaccine antigens.

The successful candidate will operate at the interface of structural biology, AI-driven discovery, and mechanism-focused validation, leading iterative design–test–learn workflows from computational design through experimental validation and structural interpretation. This includes executing and adapting computational workflows for protein design and cryo-EM data processing and analysis in HPC environments.

Working within Structural Biology and in close collaboration with AI/ML, broader Medicine Design partners, and Research Units, this role will contribute to project delivery and the development of scalable, AI‑enabled structural biology and SBDD capabilities across the discovery portfolio.

Key responsibilities include:

• Apply and adapt generative AI and computational protein design methodologies (e.g., AlphaFold, RoseTTAFold, RFdiffusion, ProteinMPNN) to design, optimize, and engineer custom structural tools – including de novo binders, fusion proteins, and fiducials – to enable structurally challenging cryo-EM targets.

• Execute and adapt computational protein design workflows in HPC environments, including data preparation, job execution, and integration into iterative design–test–learn cycles, with an emphasis on scalable, high-throughput applications for large-scale screening and discovery.

• Own end-to-end structural biology strategies, including construct engineering, sample preparation, hands-on cryo-EM structure determination, and mechanistic interpretation of complex systems.

• Apply and adapt AI/ML-enabled approaches in cryo-EM data processing and model building workflows; develop or implement automated, scalable pipelines to support analysis of large and complex datasets.

• Establish integrated data and analysis workflows that connect computational design with experimental outcomes, leveraging high-quality datasets to inform, validate, and refine next-generation AI/ML models in collaboration with experimental and computational partners.

• Communicate scientific findings to drive >Relocation assistance may be available based on business needs and/or eligibility.

  Candidates must be authorized to be employed in the U.S. by any employer.

  U.S. work visa sponsorship (such as TN, O-1, H-1B, etc.) is not available for this role now or in the future.

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  EEO & Employment Eligibility

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  Research and Development