Senior Computational Chemist, Drug Discovery
About SandboxAQ
SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors.
We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders.
At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact.
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.