Job Description
SandboxAQ is solving challenging problems with AI + Quantum for positive impact. We partner with global leaders in government, academia, and the private sector to identify applications that would benefit from quantum-based applications to current and future commercial challenges. We engage with customers early and throughout the development process to improve market fit.
Our team’s unique approach enables cross-pollination across a diverse range of fields, from physics, computer science, neuroscience, mathematics, cryptography, natural sciences and more! Our success comes from coalescing diverse talent to create an environment where experimental thinking and collaboration yield breakthrough AI + Quantum solutions. Join a culture where thought leadership, diverse talent, employee engagement, and technological impact will create the next tech uproar.
We are deeply committed to education as a means to advance quantum solutions and computing initiatives. We invest in future talent through internship programs, research papers, developer tools, textbooks, educational talks/events and partnerships with universities/talent hubs to attract multi-disciplinary talent. Our hope is to inspire people from all walks of life to be prepared for the quantum era and encourage a path in STEM.
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 RD, 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.
