Computational Chemist

The most preferred qualification is Computational Chemist with experience in catalysts.

• However, individuals with PhD degrees in Computer Science, Computer Engineering, Materials Engineering, or a related technical field, or equivalent practical experience would work as well.
• Industry experience in Machine Learning, Graph Neural Networks (GNNs), Transformers, ConvNets, Density Functional Theory (DFT), Computational Chemistry, or similar fields.
• A track record of contributing to novel methods in state-of-the-art Deep Learning, including large-scale, Graph Neural Nets, etc.
• 2+ years of experience on machine learning teams, ideally in a startup environment.
• Ability to understand business problems and build models that drive value quickly, while prioritizing research efforts accordingly.
• Skill in clearly communicating modeling setup and results at various levels of abstraction.
• Knowledge of chemistry principles and methods, with the capability to interpret results and communicate effectively.
• Good problem-solving skills, innovative thinking, and adherence to product development processes.
• Strong communication and quantitative skills.
• Minimum B2 Level of English capacity.
• Coding expertise in Python and Pythorch.