Senior Computational Chemist: AI‑Driven Drug Design

General Proximity; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

General Proximity is seeking an exceptional computational chemist to drive small‑molecule drug discovery using modern workflows and AI-enabled tools. You will collaborate closely with medicinal chemistry, biology, and DMPK teams to design from hits through lead optimization and candidate selection.

You will apply docking, MD, QSAR, FEP, and multi-parameter optimization, while leveraging AlphaFold models and cheminformatics platforms to accelerate decision-making in an AI‑driven environment.

Qualifications

• PhD in Computational Chemistry, Medicinal Chemistry, Chemical Physics, Biophysics, Cheminformatics, Physical Organic Chemistry, or a related discipline.
• Minimum of 3 years of relevant pharma/biotech experience.
• Track record of using computational chemistry to impact small-molecule drug discovery programs.
• Hands-on expertise in structure-based and ligand-based design, docking, molecular dynamics, virtual screening, QSAR, FEP/free-energy methods, pharmacophore modeling, and multi-parameter optimization.

Responsibilities

• Provide hands-on computational chemistry support for small-molecule discovery programs from target evaluation through lead nomination.
• Apply structure-based and ligand-based design approaches to guide compound design (docking, MD, pharmacophore modeling, etc.).
• Use X-ray/cryo-EM/homology/AlphaFold models to generate actionable design hypotheses.
• Partner with medicinal chemistry to interpret SAR and optimize potency, selectivity, physicochemical properties, ADME/PK, and developability.
• Translate complex modeling results into clear, practical medicinal chemistry recommendations.
• Support portfolio prioritization by evaluating tractability, ligandability, and developability risks.
• Contribute to AI-enabled design tools and data infrastructure.

Skills

High Agency

Enthusiastic

Intensity and Grit

Prosocial

Hands-on drug design

Project partnership

Education

PhD in Computational Chemistry or related field

Tools

RDKit

Python

Job description

General Proximity is seeking an exceptional computational chemist to drive small‑molecule drug discovery using modern workflows and AI-enabled tools. You will collaborate closely with medicinal chemistry, biology, and DMPK teams to design from hits through lead optimization and candidate selection.

You will apply docking, MD, QSAR, FEP, and multi-parameter optimization, while leveraging AlphaFold models and cheminformatics platforms to accelerate decision-making in an AI‑driven environment.