- Apply computational chemistry techniques to advance small-molecule drug discovery programs (Work collaboratively with chemists, biologists and multidisciplinary project team members from target assessment to hit identification, compound optimization towards clinical candidates)
- A key contributor to compound design and optimization from molecular modeling and data analysis viewpoints (Devise and implement testable hypotheses to formulate compound design strategies)
- Help with new target assessment through druggability, selectivity and/or tool compound analysis. Generate knowledge and insights at the molecular level and help to assist biophysics and biochemical assay interpretation
- Conduct scientific method development in specific cheminformatics/AI (virtual screening, model building for on-target potency or property prediction, molecule generation, etc.) or molecular modeling (SBDD or binding free energy calculation) areas applicable to drug discovery
- Apply existing machine learning or deep learning models in projects, or further develop better algorithm partnering with AI researchers if appropriate
- Have the opportunity to lead CADD initiatives or projects
- Ph. D in Computational Chemistry, Cheminformatics or a related discipline
- 5+ years of industry experience, or 3+ years in industry plus 2+ years academic post-doc experience
- Solid working knowledge of drug discovery principles including the fundamentals of medicinal chemistry, assay technology, structural biology and disease biology
- Strong communication skills and ability in formulating clear scientific hypothesis as well as articulating them during constructive dialogues with multi-disciplinary teams.
- Track record of scientific contributions in the areas of CADD illustrated by publications and/or patents.
- Appetite for molecular design fostered by a sound understanding of 3D modeling concepts (protein-ligand interactions, small molecule conformations, ...)
- Experience in AI/ML approaches including model building and statistical analysis
- Familiarity with at least one programming language (Python, R, C, C++ ...)
- Proficient with three or more of the modeling and data analysis/visualization software such as Schrodinger, MOE, OpenEye Suite, Pipeline Pilot, Knime, Spotfire, D360
- Experience in (or some of them) compound generative model, data mining and visualization, chemical space analysis (clustering, compound library assessment and HTS data triage), active-learning based virtual screening, free energy calculation, quantum mechanics calculation, or other novel computational approaches
- Fluency in written and spoken English is mandatory
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Senior Scientist, Computer-Aided Drug Design - Shanghai, 中国 - Roche
描述
The Position
Primary Purpose of Job
As a member of the AI, Data and Digital (AIDD) team, you will partner with research scientists and data experts at China Innovation Center of Roche (CICoR) on drug projects from target identification to lead discovery and early development. You will employ a combination of various capabilities including computational chemistry and cheminformatics skills, AI technologies, and molecular science knowledge to provide timely compound design and data analysis to contribute to drug projects.
Responsibilities:
Requirements:
