Materials Laboratory Scientist — AI-Driven Discovery

Google LLC; Greater London; On-site; GBP 52,000 - 76,000; Full time

Job summary

Google DeepMind in London is seeking an experimental Materials Laboratory Scientist to join our team. You will work on experimental realization, processing, and characterization of novel materials predicted by our generative AI models.

You will drive experimental workflows across laboratory synthesis and characterization, bridging traditional physical sciences with data-driven research. Working side-by-side with AI researchers, software engineers, and automation roboticists, you will help scale

Qualifications

• PhD required or equivalent practical experience.
• 2 years of experience with laboratory synthesis, preparation, or characterization of materials.
• Experience in cross-functional or interdisciplinary teams.
• Experience troubleshooting and resolving technical bottlenecks in a scientific environment.
• Publications, conference proceedings, patents, or technical white papers in Materials Science or related fields.

Responsibilities

• Characterize materials using multiple metrology platforms to validate synthesis.
• Provide experimental feedback and guide active learning pipelines with ML researchers.
• Translate benchtop protocols into high-throughput automated workflows with automation engineers.
• Execute synthesis and processing across inorganic, solid-state, thin-film, or other chemical routes to realize target materials.
• Maintain data hygiene and capture experimental telemetry and protocols in ELN/LIMS for ML datasets.

Skills

Laboratory data analysis

Cross-functional collaboration

Troubleshooting experiments

Publications experience

Education

PhD in Materials Science, Physics, Chemistry, Chemical Engineering, or related

Tools

ELN/LIMS systems

Automation/robotics tools

Job description

Google DeepMind in London is seeking an experimental Materials Laboratory Scientist to join our team. You will work on experimental realization, processing, and characterization of novel materials predicted by our generative AI models.

You will drive experimental workflows across laboratory synthesis and characterization, bridging traditional physical sciences with data-driven research. Working side-by-side with AI researchers, software engineers, and automation roboticists, you will help scale