Advanced Computational Chemist for Novel Medicines
1 month ago
SandboxAQ is at the forefront of applying AI and quantum computing to tackle complex challenges. Our mission is to collaborate with industry leaders, academia, and governments to identify opportunities where quantum-based solutions can drive significant impact.
We take a unique approach by fostering cross-pollination across diverse fields, including physics, computer science, neuroscience, mathematics, cryptography, and natural sciences. By combining expertise from various disciplines, we create an environment where experimental thinking and collaboration yield groundbreaking AI and quantum solutions.
We are deeply committed to advancing quantum solutions and computing initiatives through education and talent development. 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.
About the Role
The AI Simulation team at SandboxAQ develops new drugs and materials using a spectrum of AI and physics-based computational solutions. The AQBioSim group seeks an experienced Senior Computational Chemist to join our Drug Discovery team. This individual will be responsible for driving innovation by applying next-generation methods to support drug discovery, combining quantum, AI, and physics-based approaches like molecular dynamics and free energy perturbation.
This role offers an opportunity to work within a seasoned, agile, and multi-disciplinary group, consisting of drug hunters, computational chemists, physicists, AI experts, and software engineers. Together, you will leverage your skills to address unmet drug discovery needs.
Your Key Responsibilities:
- Apply computational solutions to address unmet drug discovery needs
- Collaborate with the AI Sim development team to improve SandboxAQ's technology and Large Quantitative Models (LQMs) to deliver deep impact at scale
- Apply the SandboxAQ computational platform to provide high-impact drug discovery solutions
- Translate insights from molecular dynamics, free energy perturbation, molecular docking, quantum, and ML methods into actionable and testable drug discovery hypotheses
- Work closely 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, generate and evaluate hypotheses to assist design decisions and influence project direction
About You
To succeed in this role, you should possess a PhD in computational physics, computational chemistry, or a related discipline. You will need 1-5 years of relevant experience, including hands-on experience with computational chemistry applied to drug discovery in the private sector, such as biotech or pharma.
Requirements:
- 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 with 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
Salary: $150,000 - $200,000 per year
Lifelancer is a talent-hiring platform that connects professionals with opportunities in Life Sciences, Pharma, and IT. If you're interested in this position, please visit the following link for more information:
https://lifelancer.com/jobs/view/3dd521a8916e2b608b1f48476da7f629
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