Senior Scientist - Associate Director, Computational Chemistry

About the Role:

We are seeking a high-impact Computational Chemist to join our integrated discovery team. In this role, you will be the computational engine of our programs, combining physics-based modeling, machine learning and structural biology to generate the quantitative predictions necessary to drive small molecule drug discovery. Beyond technical mastery, you will serve as a core strategic partner to medicinal chemists and biologists, designing compounds that move series and programs efficiently toward Go/No-Go decision points and candidate nomination.

Key Responsibilities:

• Integrate physics-based simulations with ML-driven descriptors to achieve the quantitative accuracy required to prioritize compounds for synthesis.
• Act as the computational lead on project teams, collaborating intimately with Medicinal Chemists to refine SAR and with Biologists to interpret assay results and target-ligand interactions.
• Design and prioritize chemical matter specifically aimed at hitting key program milestones, such as establishing in vivo POC, achieving selectivity windows, or optimizing ADMET profiles for candidate selection.
• Develop, validate and deploy workflows that use computational rigor to optimize the  "Design-Make-Test-Analyze" cycles.
• Synthesize complex computational data into clear, actionable design hypotheses that non-computational stakeholders can use to make high-level program decisions.

Required Qualifications:

• Ph.D. in Computational Chemistry, Biophysics, or a related field.
• 4-7+ years of experience in a biotech or pharma setting performing computational support for small molecule drug discovery.  
• Demonstrated success in a cross-functional environment, with specific examples of computational designs that directly led to the achievement of program milestones.
• Exceptional ability to communicate the "why" behind a design to a diverse scientific audience.

Preferred Qualifications:

• Design experience working in concert with medicinal chemistry teams to design synthesizable compounds that efficiently work towards defined goals of activity, affinity, selectivity, properties, etc.
• Advanced knowledge of physics-based and ML computational chemistry packages including knowing when and how to deploy various tools for maximum project impact.
• Experience working with structural biology teams to extract the most information possible from cryo-EM and x-ray crystallography experiments and using this to accelerate programs using structure-based drug discovery techniques.
• Proven experience using ML to scale physics-based insights, specifically in the context of large-scale virtual screening or FEP-guided lead optimization.
• A proven track record for innovation in structure-based small molecule drug discovery including developing and validating new workflows and techniques or expansions of existing ones.   

Skills & Competencies:

• Expert level use of structure-based small molecule drug discovery software tools including protein preparation, docking, FEP, QM, conformer selection. (Schrodinger suite, OpenEye, MOE, etc)    
• Ability to work directly in a Linux-based environment
• Familiarity with cloud computing infrastructure (AWS, GCS) is a plus
• Python scripting and prototyping experience including knowledge of key packages (RDKit, scikit-learn, numpy, pandas, pytorch, etc).