Job Description:
The ideal candidate will have extensive expertise in ligand-based and structure-based drug design methods and will have contributed to the advancement of small molecule projects through all stages of drug discovery. Of particular importance is the ability to build strong collaborations with medicinal chemists and structural biologists to help advance the drug discovery portfolio. Strong communication and collaboration skills are essential, as this position will interact closely with interdisciplinary small molecule discovery project teams. The successful candidate will help to build our Computational Chemistry capabilities and will collaborate with and support Medicinal Chemistry, Structural Biology, Bioinformatics and Discovery Sciences departments.ESSENTIAL DUTIES AND RESPONSIBILITIES: - Help to define a robust strategy to integrate advanced computational chemistry and structure-based drug design methods into small molecule drug discovery programs
- Help to build, integrate and apply computational tools and workflows to accelerate hit identification, hit-to-lead optimization, and candidate selection
- Apply state-of-the-art structure-based drug design technologies to drive hit identification, lead optimization and candidate selection in close partnership with medicinal chemists and structural biologists
- Expertise with ligand-based methods, QSAR, conformational analysis, physical chemical property modeling, molecular dynamics, free energy perturbation, molecular and quantum mechanics
- Solid understanding of medicinal chemistry, in vitro and in vivo ADME, and ability to couple computational-driven approaches to drive lead optimization beyond potency
- Strong understanding of the computational & informatics infrastructure required to support a robust SBDD/CADD capability
- Provide day-to-day scientific leadership and project support and help to build a high-performing computational drug discovery capability
- Conduct scientific presentations to senior management, project teams, and internal/external collaborators
SUPERVISORY RESPONSIBILITIES: - Help to build and hire a team of computational chemists.
EDUCATION & EXPERIENCE: - Ph.D. in computational chemistry, biophysics, physical organic chemistry, physics-based modeling, statistical modeling, ML/AI, mathematical modeling, or a related field with a clear track record of applying computational technologies and structure-based drug design to advance the discovery of small molecule therapeutics, and a minimum of 5 years of post-PhD experience; or,
- M.Sc., as above, and a minimum of 9 years of post-degree experience; or,
- B.Sc., as above, and minimum of 11 years of post-degree experience; or,
- Equivalent combination of education and experience.
ADDITIONAL SKILLS & ABILITIES: - Experience with multiple drug target classes, orthosteric and allosteric binders, fragment-based screening and optimization, covalent binders, protein degraders and/or molecular glues is strongly preferred
- Experience with machine learning/AI to rationalize SAR and recommend new molecules to test actionable hypotheses; ability to build predictive ML/AI-based models to improve potency, selectivity & ADME properties is strongly preferred
- Strong experience in cheminformatics and knowledge of computing infrastructure is a plus
- Background in library design, diversity analysis, and approaches to improve virtual screening, fragment, DEL and cell-based HTS is strongly preferred
- Working experience with software from companies such as Chemical Computing Group, Schrodinger, OpenEye, Dotmatics, Gaussian, Molsof, Chemaxon, Knime, RDKit and ICM Molsoft
- Technical leader who stays on the cutting edge to identify emerging science to advance computational platforms
- Demonstrated independent thought and creativity in science, and successful track-record in drug discovery as evidenced by patents, publications and invited presentations
- Strong written, oral and presentation communication skills
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