Materials Laboratory Scientist, Science, DeepMind

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

Materials Laboratory Scientist, Science, DeepMind

corporate_fare DeepMind place London, UK

• PhD in Materials Science, Physics, Chemistry, Chemical Engineering, or a related science discipline, or equivalent practical.
• 2 years of experience with laboratory synthesis, preparation, or characterization of materials.
• Experience working in cross-functional or interdisciplinary technical/scientific teams (e.g., across engineering, computing, materials science, or chemistry).
• Experience troubleshooting, root-cause diagnosing, and resolving technical or experimental bottlenecks in a scientific research or laboratory environment.
• Submission of scientific publications, conference proceedings, patents, or technical white papers in Materials Science, Physics, or a related discipline.

Preferred qualifications:

• Experience working with high-throughput experimental platforms, laboratory automation, or robotic instrumentation.
• Proficiency in programming (e.g., Python) for scientific data analysis, automation scripting, or instrument interfacing.
• Foundational understanding of computational materials science or exposure to machine learning workflows in physical sciences.
• Familiarity with Laboratory Information Management Systems (LIMS), electronic lab notebooks, or structured research data pipelines.

About the job

We are seeking an experimental Materials Laboratory Scientist to join our team in London. In this role, 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 laboratory throughput, build automated feedback loops, and accelerate materials discovery.

Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.

We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.

Responsibilities

• Conduct structural, compositional, and physical property characterization across a variety of metrology platforms to validate synthesized materials.
• Provide systematic experimental feedback and guide active learning pipelines in close collaboration with computational and machine learning researchers.
• Translate benchtop protocols into high-throughput automated workflows in partnership with automation engineers.
• Execute experimental synthesis and processing workflows across inorganic, solid-state, thin-film, or other chemical routes to realize target materials candidates.
• Maintain thorough data hygiene, capturing comprehensive experimental telemetry and protocols within digital laboratory systems (ELN/LIMS) to support machine learning datasets.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.