Contribute to Schrödinger’s drug discovery programs as a medicinal chemist, supporting and executing medicinal chemistry strategies to deliver high quality clinical candidates.
Locations (2)
New York, New York, United States
San Diego, California, United States
Compensation
Estimated base salary range: $150,000 - $200,000.
Responsibilities
Contribute to Schrödinger’s drug discovery programs as a medicinal chemist
Support and execute medicinal chemistry strategies to deliver high quality clinical candidates
Manage chemistry CROs to ensure efficient program execution
Collaborate with computational chemists and modelers on the application of Schrödinger’s computational platform for rapid advancement of drug discovery programs
Develops and leads innovative computational strategies that accelerate drug discovery across a Research and Development portfolio from early discovery through clinical candidate nomination.
Compensation
The annual base salary we reasonably expect to pay is $218,200.00-$298,000.00. In addition, this position offers an annual bonus with a target of 35% of the earned base salary and eligibility to participate in our equity based long term incentive program.
Responsibilities
Develops, implements, and enforces scientifically sound computational chemistry strategies that support drug discovery programs from target validation through lead optimization and candidate selection
Leads the application of molecular modeling, structure-based drug design, ligand-based design, and AI/ML approaches to enable compound design and optimization
Partners closely with medicinal chemistry, structural biology, pharmacology, and data science teams to integrate computational insights into project strategies and decision-making
Evaluates, interprets, and communicates computational results, proactively providing strategic direction to project teams and senior management on compound design and program progression
Drives innovation through the evaluation and implementation of emerging computational technologies, including generative chemistry, predictive modeling, and large-scale data analysis
Requirements
Bachelors in chemistry or related field
Masters in computational chemistry or related field
Lead computational chemistry efforts to design and model oncology-targeted therapeutics, integrating AI/ML and structure-based approaches.
Compensation
The annual base pay for this position ranges from 124,713.60 - 187,070.40 USD Annual [80% - 120% ]. Our positions offer eligibility for various incentives—an opportunity to receive short-term incentive bonuses, equity-based awards for salaried roles and commissions for sales roles.
Responsibilities
Generate testable design hypotheses integrating structural insights, SAR, and biophysical data
Apply docking, pharmacophore modeling, and data-driven design to prioritize compounds
Build, validate, and deploy predictive AI/ML models for high-throughput experiment design
Develop computational methods for antibody–drug conjugates and proximity-inducing agents
Partner with medicinal chemistry, biology, biophysics, DMPK, and safety sciences
Harness structure-based design, ligand-based approaches, and modern AI/ML to guide high-impact discovery programs across new modalities in oncology targeted discovery.
Compensation
The annual base pay for this position ranges from 124,713.60 - 187,070.40 USD Annual [80% - 120% ]
Responsibilities
Generate testable design hypotheses, integrating structural insights, SAR, and biophysical data to guide medicinal chemistry and accelerate decision-making.
Apply docking, pharmacophore modeling, and data-driven design to prioritize compounds that improve potency, selectivity, and developability.
Build, validate, and deploy predictive models using contemporary toolkits to support high-throughput experiment design and increase hit-to-lead success.
Develop and refine computational methods for antibody–drug conjugates and bifunctional, proximity-inducing agents, expanding design capabilities beyond small molecules.
Partner closely with medicinal chemistry, biology, biophysics, DMPK, and safety sciences to align models with mechanistic understanding and project goals.
Requirements
Ph.D. in computational chemistry or a related field
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