Materials Laboratory Scientist, Physical Properties, DeepMind

Materials Laboratory Scientist, Physical Properties, DeepMind

corporate_fare DeepMind place London, UK

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• PhD in Physics, Materials Science, or Electrical Engineering, a related field, or equivalent practical experience in experimental condensed matter physics.
• 2 years of experience with physical property characterization (e.g., cryogenic transport, magnetometry, dielectric, thermal, and thermoelectric properties), low-noise measurement techniques, precision instrumentation, and data analysis.
• Experience with lab operations, instrument health, and laboratory safety protocols (e.g., vacuum systems, high-voltage equipment, and the safe handling of hazardous chemical precursors).

Preferred qualifications:

• Experience with laboratory automation, robotics, or high-throughput experimental workflows and with designing "closed-loop" experiments where measurement data automatically triggers the next experimental step.
• Experience with a wider range of characterization techniques (e.g., XRD, SEM, photophysics) and lab management software or managing chemical inventories and safety documentation.
• Experience in a materials research and development lab in a post-doctoral or industry setting.
• Excellent organizational skills, and in troubleshooting experimental issues to produce high-quality data with attention to detail.
• Proven track record of impactful research, demonstrated by publications in peer-reviewed journals or recognized contributions to the field.

About the job

DeepMind is establishing the Materials Discovery Laboratory, an automated facility designed to bridge the gap between AI predictions and physical reality. This lab will serve as the engine of our materials research program, combining high-throughput synthesis and characterization with advanced robotics to create a closed-loop discovery system.

In this role, you will lead the validation of our AI discovery engine, establishing the ground truth for novel materials. You will develop high-fidelity characterization approaches and partner with engineering teams to streamline these measurements and scale their throughput.

Responsibilities

• Develop and perform high-fidelity cryogenic electronic transport, magnetic, optical, thermal, and mechanical measurements to validate critical material properties.
• Move beyond manual point-measurements by developing rapid measurement processes that can manage batches of samples, enabling faster feedback loop to the AI models.
• Collaborate with a wider team, implement data analysis pipelines that extract physical properties from raw data and define metrics for applicant materials.
• Partner with the engineering team by providing the scientific requirements and experimental feedback needed to help design and test hardware for sample loading and measurement, maximizing instrument utilization.

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