Computational Chemist, Drug Discovery

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Requirements:

• 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 biotech, pharma, or related industries.
• A deep commitment to critical thinking—comfortable questioning methodologies, challenging assumptions, and refining approaches to improve predictive accuracy.
• A collaborative mindset, working closely with colleagues to identify problems and communicate technical solutions clearly and effectively.
• A hands-on mentality, eager to dive into complex problems and drive projects to completion.
• Experience in structure-based drug design and familiarity with ligand-based drug design methods.
• Experience with GPU-accelerated MD codes like OpenMM.
• Proficiency in the Python data science stack (NumPy, Pandas, SciPy, etc.).
• Familiarity with ligand-protein free energy of binding prediction methods such as Free Energy Perturbation (FEP) or similar.
• Experience running computational chemistry/quantum simulations on high-performance computing (GPU) environments for corporate R&D, innovation labs, or academic research.
• A passion for solving scientific problems in chemistry and biology through computational and data-driven methods, with a commitment to rigorous validation and scientific integrity.

Responsibilities:

• Apply computational solutions to address unmet drug discovery challenges, questioning assumptions and rigorously validating results.
• Work closely with the development team to enhance SandboxAQ’s unique technology and Large Quantitative Models (LQMs) for large-scale impact.
• Apply SandboxAQ’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.