This post will be open until the position is filled.
Qualifications
Required:
Track record in deep Learning research, as evidenced by a PhD or similar research experience in the field.
Experience designing and optimizing new architectures and algorithms and running experiments and analyses to study their performance.
Experience in Python software development, ideally demonstrated by published software projects (e.g., github).
Experience in developing and implementation of deep learning systems (e.g., in PyTorch or JAX).
Ability to work in an interdisciplinary collaborative environment, through effective communication of technical concepts to non-experts from different technical backgrounds.
Preferred:
Experience working with graph data, equivariant networks, reinforcement learning, generative models, and/or large language models (LLMs).
Experience with developing deep learning models with molecular data.
Track record of publications in ML conferences and/or scientific journals.
Responsibilities
Contribute to and drive an ambitious, high-impact, research agenda in AI for materials.
Design and develop new deep learning models and algorithms.
Write code to run and evaluate large scale ML experiments.
Work with internal and external partners to deploy and evaluate models and workflows.
Prepare technical papers, presentations, and open-source releases of research code.