Senior Researcher in Deep Learning - AI for Science

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Microsoft Research AI for Science is seeking a talented researcher to join our mission of accelerating scientific discovery through AI. In the materials team, we are building next generation foundational AI capabilities to accelerate the design of novel materials. You can learn more about our AI emulator MatterSim and generator MatterGen in our blog.

This role is an exceptional opportunity to shape the future of materials design with cutting-edge methodology and large-scale data generation. You will join a highly collaborative, interdisciplinary, and diverse team of researchers and engineers to push the frontier of foundational AI models for materials.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more, and we’re dedicated to this mission across every aspect of our company. Our culture is centred on embracing a growth mindset and encouraging teams and leaders to bring their best each day. Join us and help shape the future of materials design.

This post will be open until the position is filled.

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.

#Research #AI for Science

• 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.