Senior Scientist, AI‐Enabled Structural Biology
$93,600–$156,000 year
On-siteGroton, Connecticut, United States
Job Summary
Senior Scientist, AI-Enabled Structural Biology at Pfizer. Lead AI-driven structure-based discovery by integrating AI-guided protein design, structure prediction, and cryo-EM data processing; translate computational approaches into experimentally tractable solutions and leverage AI/ML to accelerate structural discovery. Apply de novo designed proteins, engineered constructs, scaffolds, and conformational stabilizers to enable structurally challenging cryo-EM targets for SBDD across modalities. Own end-to-end structural biology strategies, including construct engineering, sample preparation, cryo-EM structure determination, and mechanistic interpretation; develop scalable AI-enabled data analyses and automated pipelines; collaborate with AI/ML and broader Medicine Design partners to deliver project outcomes and reusable capabilities; communicate findings to drive data-informed decisions and contribute to scientific reports and publications.
Required Qualifications
- Ph.D. in Structural Biology, Biochemistry, Biophysics, Computational Biology, or closely related discipline with demonstrated innovation in protein design and engineering during Ph.D. or postdoctoral experience
- Hands-on expertise in cryo-EM including data processing workflows and familiarity with AI/ML-enabled approaches with interest in automation and scalable data analysis
- Proficiency with current structure prediction and protein design software (e.g., AlphaFold, RoseTTAFold) and familiarity with generative models (e.g., RFdiffusion, ProteinMPNN)
- Experience working with HPC environments to execute and adapt computational protein design and cryo-EM workflows at scale, including data preparation and job execution, and scripting (e.g., Python) to automate workflows for high-throughput, large-scale screening
- Strong experience in experimental triage for challenging or conformationally heterogeneous systems, with ability to integrate structural and functional data to evaluate construct or binder performance and mechanistic impact
- Proven ability to work effectively in cross-functional, multidisciplinary teams, with strong written and verbal communication skills and track record of presenting complex scientific findings
Desired Qualifications
- Breadth of experience across multiple target classes (e.g., GPCRs, transporters, ion channels, dynamic protein complexes)
- Mentoring or coaching junior scientists or collaborators
- Demonstrated scientific leadership
- Experience developing scalable or generalizable experimental strategies
- Familiarity with pharmacology, biochemistry, or biophysical assays related to construct integrity and functional relevance
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