About the Role

SandboxAQ’s AI Simulation team develops new drugs and materials using a spectrum of AI and physics-based computational solutions. Our AQBioSim group is looking for a senior computational chemist to join our Drug Discovery team. This person’s responsibility will be to drive innovation by applying next-generation methods to support drug discovery by combining quantum, AI, and physics-based methods like molecular dynamics and free energy perturbation. These skills will be leveraged within a seasoned, agile, and multi-disciplinary group, including drug hunters with an excellent track record in drug discovery, computational chemists, physicists, AI experts, and software engineers.

What You’ll Do

• Apply computational solutions to address unmet drug discovery needs
• Work closely with the AI Sim development team to improve SandboxAQ’s unique technology and Large Quantitative Models (LQMs) to deliver deep impact at scale
• Apply SandboxAQ computational platform to provide high-impact drug discovery solutions
• Translate insights from molecular dynamics, free energy perturbation, molecular docking, quantum, and ML methods in actionable and testable drug discovery hypothesis  
• Work in close collaboration with ML experts and cross-functional teams to prototype and scale cutting-edge, impactful drug design solutions.
• By deploying and developing computational methods and workflows, you will generate and evaluate hypotheses to assist design decisions and influence project direction. 
• This is an opportunity to directly contribute to the discovery of novel innovative medicines by applying computational chemistry techniques on teams with experienced multidisciplinary drug hunters.

About You

• PhD in computational physics, computational chemistry, or a related discipline
• 1-5 years of relevant experience including hands-on experience with computational chemistry applied to drug discovery in the private sector, like biotech or pharma
• Experience in structure-based drug design and familiarity with ligand-based drug design methods
• Experience with GPU-accelerated MD codes like OpenMM
• Experience with the Python data science stack (Numpy, Pandas, Scipy, etc.) 
• Familiarity with ligand-protein free energy of binding prediction methods like Free Energy Perturbation (FEP) or similar.
• Familiarity running computational chemistry / quantum simulations on high-performance computing (GPU) environments for corporate R&D, innovation labs, or academic research.
• An interest in solving scientific problems in chemistry and biology via computational and data-driven methods
• A drive to cooperate with colleagues to identify problems and communicate technical solutions in an accessible manner
• Hands-on mentality & comfortable with getting deep into the technical weeds of highly complex problems, and a track record of driving projects to completion

The US base salary range for this full-time position is expected to be $133k - $210k per year. Our salary ranges are determined by role and level. Within the range, individual pay is determined by factors including job-related skills, experience, and relevant education or training. This role may be eligible for annual discretionary bonuses and equity.