Computational Chemist/CADD Scientist

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

At Reverie Labs, we’re building a pharmaceutical company from the ground up using computation. We’re a team of scientists and machine learning researchers using cutting-edge tools to design new medicines. We are looking for a computational chemist with a strong background in using computational tools to do structure-based drug discovery. You will leverage these tools both to develop new datasets for machine learning and to have a direct impact on multiple internal and external drug discovery projects. You will need to communicate your insights and experience to the team, and work with machine learning scientists to help develop and improve models for important molecular properties. From hit-finding to lead optimization to candidate selection, you will work closely with the entire Reverie team to design and optimize potential new medicines.

Responsibilities:

• Leverage Reverie's proprietary computational tools for cheminformatics, docking, molecular dynamics (MD), quantum mechanics (QM), and machine learning (ML) to design and optimize small-molecule drug candidates.
• Work closely with machine learning engineers and medicinal chemists to make key decisions for internal and external drug discovery projects.
• Take the lead in the end-to-end development and application of Reverie's computational chemistry and cheminformatics platform.
• Lead the dissemination of CADD/SBDD knowledge within our multidisciplinary team.

We are looking for candidates with the following qualifications:

• PhD in computational chemistry, structural biology, medicinal chemistry, or a related discipline.
• Experience with using commercial and preferably open-sourced computational chemistry tools (e.g. OpenMM, RDKit, etc.) as part of a structure-based small-molecule drug discovery campaign.
• Extensive knowledge of computational chemistry techniques such as MD (including FEP), docking, QM, virtual library design, etc.
• Strong scientific programming skills using Python.

Hands-on experience in one or more of the following fields will be particularly appreciated:

• Development of free-energy methods and workflows using OpenMM or AmberTI.
• Application of enhanced sampling methods to the study of protein conformational dynamics and/or protein-ligand interactions.
• Application of QM calculations to investigate the conformations and energetics of drug-like small molecules.