AI for Science Residency – Machine Learning Resident  

Drive an ambitious, high-impact, research agenda on machine learning for materials. Develop efficient and expressive machine learning models that address fundamental materials science problems. Work with domain experts to develop realistic machine learning metrics and benchmarks. Prepare technical papers and presentations. Contribute to building large-scale infrastructure for data generation, model training and inference. Keep up-to-date with latest developments in the field. PhD in computer science, machine learning, computational materials science, physics, or related area. Track record of publications at top-tier conferences or journals (e.g., NeurIPS, ICML, ICLR, Nature/Science or relevant sub-journals). Strong coding ability and proficiency in collaborative code development. Ability to quickly iterate between ideation, implementation and evaluation of new research ideas. Ability to work in an interdisciplinary collaborative environment, through effective communication of technical concepts to non-experts from different technical backgrounds. Experience working on generative models. Experience working on (materials) science problems. Experience with agent-driven research and code development.