As a Machine Learning Researcher, you will play a crucial role in a dynamic and innovative team focused on discovering and commercializing groundbreaking materials to combat climate change. Your responsibilities will include contributing to the development of large-scale generative models, creating new graph neural network architectures for atomic systems, and collaborating with computational chemists to enhance existing approaches. Additionally, you will leverage unstructured data to develop supplementary models for low-data domains and work closely with experimental scientists to test new materials in real-world applications.
What the Company is Looking For
PhD or equivalent experience in machine learning research
Strong background in algorithms, data structures, and code standards
Hands-on experience with deep learning and PyTorch
Familiarity with performance optimization of deep learning models
Experience with distributed training and remote computing environments
Interest in computational approaches to molecule and materials design
Willingness to collaborate with experimental scientists
Bonus: Experience with graph neural networks or computational methods on graphs and 3D data
Desirable Things the Company is Looking For
Experience working with graph neural networks or message passing neural networks
Interest in high-impact research at the intersection of machine learning and materials science
Ability to collaborate effectively with a diverse team of experts
Strong communication skills and a proactive approach to problem-solving