Lead Scientist - Small Molecule Digital Chemistry

Role Summary

The Lead/Principal Data Scientist – Small Molecule Digital Chemistry will contribute to the ISCM team's effort towards exploring, implementing, and applying computational chemistry and cheminformatics methods and tools to achieve Digital Chemistry and Design goals. They will work on advanced molecular modeling and computational drug design for small molecules and engage in drug discovery projects from early discovery to scale-up, leading the development of complex workflows to prepare structural data, generate 2D/3D models, execute virtual screening, and optimize small molecule designs. The role requires proficiency in modern 3D modeling tools for structure- and ligand-based drug design, scientific programming, machine learning methods, and HPC/cloud computing, with an in-silico first mindset.

Responsibilities

• Advance Small Molecule pharmaceutical project portfolio through computational chemistry method applications
• Develop digital chemistry processes and workflows to address pharmaceutical project needs.
• Provide pharmaceutical project teams with computational strategies to inform, influence, and prioritize designs for potency/selectivity and improve ADME/Tox endpoints
• Conceptualize approaches, identify capability gaps, and set goals within ISCM.
• Represent ISCM as a scientific lead on cross-functional teams that include discovery and research IT organizations
• Maintain a well-documented, reusable codebase, and traceable model history
• Maintain scientific and technical expertise through familiarity with scientific literature and attending conferences.
• Participate in the evaluation of external and internal capabilities and facilitate collaborations with external partners
• Present results to interdisciplinary teams of experimental, modeling scientists and machine learning colleagues

Qualifications

• Ph.D. with 6+ years of relevant experience required; M.Sc. with 8+ years can be considered. Degree in Computational Chemistry, Cheminformatics or related quantitative field preferred
• Relevant experience includes:
  • Research experience in the field of small molecule drug discovery within industry or academia (industry preferred) as demonstrated by publications or presentations documenting impactful application of computational chemistry methods.
  • Proficiency in general molecular modeling techniques (e.g. docking, molecular dynamics simulations, pharmacophore search, structure/ligand-based design).
  • Hands on experience with molecular modeling software (e.g. Maestro, OpenEye, Rosetta, etc.) and cheminformatics packages (e.g. RDKit)
  • Familiarity with QSAR/QSPR modeling, cheminformatics, and AI/ML methods.
  • Proficiency in scripting or programming languages such as Python or C++
• Ability to perform in-depth data analysis and develop processes to solve complex problems
• Excellent written and oral communication skills, including presentation skills to diverse audiences
• Detail oriented with strong documentation skills
• Familiarity and working experience with a breadth of tasks of the Design-Make-Test-Analyze drug discovery cycle – highly preferred

Additional Requirements

• Up to 10% overnight travel may be required.