Microsoft Cambridge Residency Programme - Computational Materials Scientist 

Taiwan, Taoyuan City 

714285149

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

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

Required:

• PhD in Materials Science, Solid-state Physics, Computational Chemistry, or a related field, or equivalent training and experience in research.
• Strong background in theoretical and computational material science.
• ExperiencewithDFT methods and workflows.
• Strong software development skills (e.g. in Python)
• Excellent written and verbal communication skills.
• Ability to work independently and as part of a cross-disciplinary team.
• Experience with molecular dynamics simulation.

Preferred Qualifications:

• Familiarity with phase-change materials, thin-film materials, or device physics.
• Experience with solid-solid interface simulations.
• Experience with high-throughput simulation workflows.
• Familiarity with DFT methods for optical properties.
• Experience with amorphousphase simulationsand analysis.
• Understanding of free energysimulationmethodssuch as meta-dynamics.
• Experience working with experimental collaborators and with automated laboratory environment.
• Demonstrated communication skills through impactful academic publications.

• Development of advanced simulation workflows for complex materials and interfaces.
• Develop and refine computational models for atomic-scale interactions and material properties.
• Contribute to the creation and curation of datasets supporting model development and validation.
• Collaborate within a multidisciplinary team—including experts in machine learning, storage materials, and experimental science—to enhance methods for analysing and predicting material behaviour.
• Support the implementation of scalable, automated approaches for materials discovery and characterisation.
• Communicate research progress and contribute to scientific publications and presentations.