Job Description

About Us:

Grafton Biosciences is a stealth-mode, San Francisco-based biotech startup focused on solving disease through groundbreaking innovations in early detection and therapeutics. We are combining breakthroughs in synthetic biology, machine learning, and manufacturing to fundamentally extend healthy human lifespans. We’re looking for passionate team members who want to shape the future.

Role Summary:

We are seeking an experienced Computational Chemist to conduct and analyze advanced molecular simulations of proteins, RNA, and small molecules. The ideal candidates will apply their expertise in molecular dynamics and enhanced sampling techniques to provide critical insights into molecular interactions, conformational dynamics, and binding phenomena, contributing directly to our research objectives.

Key Responsibilities:

• Design, execute, and analyze molecular simulations (MD and/or QM) of biomolecular and chemical systems.
• Investigate molecular interactions, binding affinities, and reaction mechanisms.
• Employ enhanced sampling methodologies (e.g., metadynamics, WESTPA) to study complex molecular events.
• Utilize classical MD software (e.g., LAMMPS, AMBER, GROMACS, OpenMM) and DFT packages (e.g., Quantum ESPRESSO, CP2K, Gaussian).
• Apply or collaborate on the integration of machine learning techniques (e.g., VAMPnets) for simulation analysis.
• Manage and execute simulations on cloud computing platforms (Azure/AWS).
• Collaborate with interdisciplinary teams, including machine learning and HPC specialists.
• Maintain currency with scientific literature and advancements in computational chemistry.
• Document and present research findings internally and externally.

Essential Qualifications:

• Ph.D. in Computational Chemistry, Biophysics, Chemical Physics, or a closely related discipline. (A Master's degree with significant relevant experience, or equivalent demonstrated practical experience, will also be considered).
• Demonstrated experience in molecular simulations of proteins, nucleic acids, and/or small molecules.
• Proficiency with classical Molecular Dynamics (MD) theory and software (AMBER, GROMACS, LAMMPS, or OpenMM).
• Experience with enhanced sampling techniques (e.g., metadynamics).
• Working knowledge of Density Functional Theory (DFT) and relevant software (Gaussian, Quantum ESPRESSO, or CP2K).
• Strong scripting skills in Python.
• Proficiency in Linux environments and Bash scripting.
• Experience with scientific computing on cloud platforms (Azure or AWS).
• Excellent analytical, problem-solving, and communication skills.

Preferred Qualifications:

• Experience with machine learning applications in molecular simulation (e.g., VAMPnets, Markov State Models).
• Familiarity with generative models for folding of proteins or other biomolecules.
• Prior experience in an industrial research environment (e.g., drug discovery, materials science).

What We Offer:

• Competitive compensation.
• Comprehensive health, dental and vision coverage.
• Opportunity to define a new therapeutic‑design paradigm and see your work progress through the clinic.

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