Track record in Digital Organic Chemistry, Computational Chemistry or related field, as evidenced by a PhD or similar research experience.
Strong understanding of Digital Chemistry, Chemoinformatics and/or applied Quantum/Computational Organic Chemistry data and methods, including applications and limitations.
Knowledge of contemporary Organic Chemistry.
Publication record in relevant Chemistry journals and/or ML conferences.
Either hands on experience in organic synthesis, or track record of collaborating with experimental collaborators.
Experience in Python coding, ideally demonstrated by published software projects (e.g., github).
Preferred:
Experience working with graph or geometric deep learning, reinforcement learning, and/or generative models is a plus.
PostDoc or more senior academic experience or industrial research experience.
Responsibilities
Contribute to and drive an ambitious, high-impact, AI research agenda in digital organic chemistry.
Use your Chemistry expertise to develop and evaluate models, methods and build new training and testing datasets.
Write scripts and code to handle, process and analyze small and large chemical datasets.
Work with internal and external partners to deploy and evaluate models and work-flows.
Prepare technical papers, presentations, and open-source releases.
Working on a day-to-day basis with an international and interdisciplinary research team on one overarching research goal.