A materials science research position at the interface of ML accelerated materials discovery and synthesis, focusing on simulations of materials and interfaces, for AI Infrastructure.
This is a 24-month fixed-term post-doctoral Residency position within the Future AI Infrastructure research group at Microsoft Research Cambridge (UK), as part of our “Materials for the Cloud” project to improve the cost, performance or sustainability of future AI cloud infrastructure. This is an extraordinary opportunity to work at the forefront of materials science in collaboration with researchers from Microsoft Research (AI for Science) to utilise foundational models for predicting new materials with exciting properties. In addition to this, you will benefit from working closely with experimental researchers and in-house materials synthesis to further refine these models using lab generated data.
We are looking for a researcher with skills in computational materials science, DFT simulations for materials, and molecular dynamics, to design and refine workflows for complex materials such as amorphous-crystalline coexistence, solid-solid interfaces, and thin-films.
The role will focus on developing and improving simulation workflows for amorphous and crystalline materials, including using the MatterSim model and high-throughput data generation pipelines. You will work closely with researchers and experimentalists in materials science, AI, and simulation, contributing to advancing simulation methods for complex materials, including the development of new approaches for modelling atomic interactions, generating and analysing amorphous and interfacial structures, and implementing high-throughput workflows. You will contribute to building robust datasets, improving model accuracy, and enabling systematic exploration of material properties to support innovative materials design and