Semiconductor Material Science Research Scientist, DeepMind

Overview

In this role you apply advanced computational methods to predict semiconductor properties and understand structure–property relationships at the atomic scale and at interfaces. You will work across theory and experiment, identifying promising materials and collaborating with experimentalists to realize them in the lab. You will leverage first-principles simulations and data-driven approaches to accelerate materials discovery and impact product-driven AI initiatives. This role offers an opportunity to shape how computation drives experimental validation and material innovation at scale.

Responsibilities

• perform and analyze DFT, DFPT, and MD simulations to predict semiconductor properties (band gaps, defect levels, dielectric constants, interfacial properties)
• investigate structure–property relationships at atomic scales and interfaces with semiconductors
• bridge theory and experiment by identifying materials candidates and collaborating with experimentalists for synthesis
• develop and apply computational workflows to enable materials discovery and data-driven insights
• contribute to high-throughput computational efforts and possibly ML-based property predictions

Key requirements

• PhD in a related field or equivalent practical experience
• experience with first-principles methods (DFT, DFPT)
• programming experience in Python for workflow management, data analysis, and automation
• experience with computational packages such as VASP or Quantum ESPRESSO used in industry or academia
• strong problem-solving and collaboration skills
• cross-functional collaboration
• effective communication with experimentalists
• problem-solving and initiative
• DFT
• DFPT
• MD (e.g., classical MD)

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