Job Description

Principal Scientist, Computational Chemistry

Boulder, Colorado, United States

Cogent Biosciences is a publicly traded biotechnology company focused on developing novel precision therapies to treat a broad range of patients with unmet medical needs. Cogent's lead program, bezuclastinib, is designed to selectively and potently inhibit exon 17 mutations found within the KIT receptor tyrosine kinase, including KIT D816V. KIT D816V is responsible for driving a rare and serious condition called Systemic Mastocytosis, and exon 17 mutations are also found in patients with gastrointestinal stromal tumors (GIST), a type of cancer with strong dependence on oncogenic KIT signaling. Bezuclastinib has exhibited promising initial data across all three trials: APEX in AdvSM, SUMMIT in NonAdvSM, and PEAK in GIST, including an encouraging safety profile across 600+ patients in single-agent and combination dosing.

We are seeking an Experienced Computational Chemist who thrives at the intersection of molecular modeling, data-driven decision making, and innovative drug design. In this role, you will directly influence discovery programs by generating actionable structure-based insights, developing predictive models, and partnering with multidisciplinary teams to guide molecular design from hits to optimized leads. This is a full-time, on-site position based at our R&D facility in Boulder, Colorado.

Responsibilities:

• 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

Target Bonus: 15% Exact compensation will vary based on skills, experience, and location.

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