Principal Scientist, Computational Chemistry

• Apply structure‑based and ligand‑based drug design methods—including docking, protein modeling, and a range of computational techniques—to support projects from hit discovery through lead optimization.
• Collaborate with project team members, engaging them in iterative structure‑based drug design cycles to generate hypotheses, evaluate targets, triage hits, and guide SAR exploration.
• Present modeling insights clearly and effectively to cross‑functional project teams, ensuring data is interpreted in the right context.
• Develop, refine, and maintain robust computational workflows on HPC Linux environments, enabling scalable execution of large‑scale simulations.
• Train and mentor colleagues on computational chemistry tools, cheminformatics standards, data formats, and key workflow practices.

Qualifications:

• Ph.D. in Computational Chemistry or a related field, with 3+ years of relevant industrial experience.
• Expertise in structure‑based design, docking, virtual screening, pharmacophore modeling, and other computational approaches for lead optimization.
• Expertise in MOE modeling software, with working knowledge of other commercial and open‑source computational chemistry platforms preferred.
• Strong hands‑on experience with cheminformatics platforms and tools, including Spotfire.
• Strong programming skills with experience in building custom scripts or automated pipelines, is a plus.
• Proficiency in Linux/UNIX, shell scripting, and HPC frameworks (e.g., SLURM, LSF, PBS/Torque).
• Experience optimizing large computational workloads on cluster or cloud infrastructure.
• Familiarity with molecular representations and cheminformatics standards (SMILES, SDF, descriptors, fragment‑based encodings).
• A solid publication record and excellent scientific communication skills.
• Proven effectiveness working within cross‑functional, data‑driven scientific teams.

Salary Range:

$165k - 190k USD