Senior Computational Chemist, Drug Discovery

About SandboxAQ

Sandbox

AQ 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 Sandbox

AQ, 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.

Sandbox

AQ’s AI Simulation team develops novel drugs and materials by integrating AI and physics-based computational solutions. Our AQBioSim group seeks a computational chemist who will not only apply cutting‑edge methodologies but also critically assess and refine computational approaches. This individual will challenge assumptions, ask "why" when interpreting results, and ensure the reliability and accuracy of findings rather than blindly trusting outputs.

This UK-based role will drive innovation by combining quantum, AI, and physics-based methods—such as molecular dynamics and active learning free energy perturbation—to advance drug discovery. Working within a highly skilled and multidisciplinary team, including drug hunters with a strong track record in drug discovery, computational chemists, physicists, AI experts, and software engineers, you will play a key role in shaping the future of computational drug design.

• Apply computational solutions to address unmet drug discovery challenges, questioning assumptions and rigorously validating results.

• Work closely with the development team to enhance Sandbox
  
  AQ’s unique technology and Large Quantitative Models (LQMs) for large‑scale impact.

• Apply Sandbox
  
  AQ’s computational platform to provide high‑value drug discovery solutions while critically evaluating its methodologies and results.

• Translate insights from molecular dynamics, free energy perturbation, molecular docking, quantum, and ML methods into actionable, testable drug discovery hypotheses.

• Collaborate closely with ML experts and cross‑functional teams to prototype and scale innovative drug design solutions.

• Develop and deploy computational methods and workflows to generate and evaluate hypotheses, guiding design decisions and influencing project direction.

• Challenge conventional thinking by critically assessing and interpreting computational outputs, ensuring robust scientific conclusions.

• Directly contribute to the discovery of innovative medicines by integrating computational chemistry techniques into multidisciplinary drug discovery teams.

• Generate and evaluate hypotheses to assist design decisions and influence project direction by deploying and developing computational methods and workflows.

• PhD in computational physics, computational chemistry, or a related discipline.

• 3-5 years of relevant experience, including hands‑on experience with computational chemistry applied to drug discovery in biotech, pharma, or related industries.

• Excellent communication skills and record of fostering successful internal collaboration and effective external partnerships.

• A deep commitment to critical thinking - comfortable questioning methodologies, challenging assumptions, and refining approaches to improve predictive accuracy.

• A drive to cooperate with colleagues to identify problems and communicate technical solutions clearly and effectively.

• A hands‑on mentality & comfortable with getting deep into the technical weeds of highly complex problems.

• Track record of driving projects to completion.

• Proficiency in structure‑based drug design and familiarity with…