You will

• Develop and refine sampling methods and protocols to explore diverse protein conformational landscapes, focusing on large conformational transitions critical to drugging previously undruggable targets.
• Apply advanced sampling techniques such as metadynamics, weighted ensemble, and replica exchange to identify and characterize challenging targets like cryptic pockets and protein-protein interfaces.
• Utilize our cluster of 1,000s of GPUs and 10,000s of CPUs for massive experimentation, with an easy-to-use Python API that manages autoscaling, parallelization, and data pipelining behind the scenes.
• Work closely with our ML researchers, computational chemists, and medicinal chemists to validate and quickly deploy improvements to our ML/MD platform for our chemists’ daily use on our internal drug programs and collaborations.

You are

• A PhD-level researcher with a proven track record of applying sampling methods to complex and challenging targets, evidenced by publications, presentations, or significant work experience.
• Strong theoretical understanding of the various sampling methodologies and their practical applications, with demonstrated ability to innovate and adapt these methods.
• A skilled programmer, preferably in Python, such that you can quickly implement your research ideas and analyze their performance across our benchmark suite.

What we offer

• The opportunity to work on challenging, high impact computational chemistry research that is immediately deployed to accelerate the discovery of new medicines.
• A world-class, tight-knit team of good-hearted people across software, machine learning, computational chemistry, medicinal chemistry, and biology.
• Competitive salary and equity. Medical, dental, and vision insurance, and a 401(k) program.