Senior ​/ Principal Scientist, Structural Biology — Target Druggability & Structure-Based Drug Design

Schrödinger seeks a Senior or Principal Scientist in Structural Biology (Target Druggability and Structure-Based Drug Design) to join us in our mission to transform the discovery of therapeutics and materials!

Schrödinger has pioneered a physics-based software platform that enables discovery of high-quality, novel molecules for drug development and materials applications more rapidly and at lower cost compared to traditional methods. The software platform is used by biopharmaceutical and industrial companies, academic institutions, and government laboratories around the world. Our multidisciplinary drug discovery team also leverages the software platform to advance collaborative programs and its own pipeline of novel therapeutics to address unmet medical needs.

As a member of our Structural Biology and Target Enablement team in our Therapeutics Group, you’ll partner with Molecular Pharmacologists, Biologists, Medicinal Chemists, and Computational Chemists to define target tractability strategies, identify and validate novel and cryptic binding sites, and design and supervise experimental campaigns to solve unprecedented structures that unlock previously intractable targets. Sitting at the interface of computation and experiment, you’ll be as comfortable proposing in silico-predicted binding site hypotheses as you are designing and executing the experimental structural biology strategies to test them.

• A scientist with a track record of success in assessing and expanding oral drug tractability for challenging and undrugged targets
• A structural and computational biology expert who’s familiar with Schrödinger’s platform (Glide, FEP+, Bio Luminate, Prime, etc.) or comparable structure-based design software
• A veteran of computational-experimental hybrid work in biotech, pharma, or an SBDD-focused software company
• A researcher who has worked on modality-switch programs (e.g., biologic-to-small-molecule or PROTAC/molecular glue strategies)
• An excellent scientific communicator who has presented target tractability assessments to senior stakeholders and defended hypotheses under scientific scrutiny

• Define druggability hypotheses for difficult-to-drug targets by integrating structural, computational, biophysical, and pharmacological evidence
• Apply and advance computational methods, including AI/ML approaches, for structure prediction and refinement, small-molecule binding site identification (including cryptic and transient pockets), pocket druggability scoring, and conformational sampling of target ensembles
• Translate structural and computational insights into actionable hypotheses for medicinal chemistry and biology teams, proposing specific experiments (biophysical, structural, or computational) to test and de-risk emerging druggability hypotheses
• Evaluate and integrate emerging methods (e.g., generative structure prediction, cryptic pocket detection, MD-based ensemble docking, AI-based binding site/ligandability prediction) into practical workflows
• Present target tractability assessments to project teams, portfolio review committees, and leadership, communicating complex structural/computational rationale clearly to non-specialist audiences
• Lead experimental structural biology efforts on active target enablement and drug discovery programs, managing work at external CROs, collaborating with our internal Structural Biology team, and/or directly performing hands‑on experiments at our internal laboratory
• Contribute to Schrödinger's broader platform strategy, feeding practical, target‑tractability‑driven requirements back into internal software and methods development

• PhD (or equivalent industrial experience) in Structural Biology, Biophysics, Computational Chemistry, or a related discipline
• Deep, hands‑on expertise in structure‑based drug design, including practical experience with cryptic/transient binding site identification and pocket druggability assessment
• Working fluency in modern computational structural biology methods, such as AI‑based structure prediction, MD‑based conformational sampling, binding site/pocket detection algorithms, and structure…