Materials Laboratory Scientist

Snapshot

Science is at the heart of everything we do at Google DeepMind. From the beginning, we took inspiration from science to build better algorithms, and now, we want to use our toolkit to accelerate scientific discovery. By bringing together specialists with backgrounds in machine learning, computer science, physics, chemistry, biology and more, we’re optimistic that we can build new methods that will push the boundaries of what is possible and help solve the biggest problems facing humanity.

About us

Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.

The role

Google DeepMind (GDM) is pursuing a ground-breaking research program in materials, aiming to accelerate the discovery of new functional materials by combining the predictive power of artificial intelligence (AI) with automated experimentation. The team is establishing experimental capacity to create a closed-loop, AI-driven discovery engine. This lab will be crucial for synthesizing and characterizing novel materials, validating AI-generated hypotheses, and generating high-quality data to refine our models.

We are seeking an exceptional and highly motivated expert in solid-state synthesis and characterization to lead the design, outfitting, and management of this new laboratory. This is a founding role with a unique blend of scientific leadership, hands-on experimental work, and strategic input. You will be instrumental in building our experimental capabilities from the ground up and refining the critical in-silico to experiment feedback loop that is at the heart of our mission.

Key responsibilities

• Lab Design & Setup: Lead the strategic planning, design, equipment selection, and commissioning of a new materials synthesis and characterization laboratory.
• Experimental Execution & Leadership: Independently plan and execute experimental workflows to synthesize and characterize novel inorganic materials proposed by our AI models.
• Workflow Automation: Collaborate with engineers and AI researchers to develop and implement high-throughput and automated experimental workflows, from precursor handling to data analysis.
• Data Integrity & Feedback Loop: Ensure the generation of high-quality, reproducible experimental data. Play a key role in structuring and feeding this data back to the AI team to create a rapid and effective discovery cycle.
• Lab Management, Health & Safety: Establish the operations management structure and working practices of the lab, including instrument maintenance, administration of consumable inventory, and establishing and enforcing comprehensive health and safety protocols.
• Cross-functional Collaboration: Work closely with AI researchers, computational scientists, and software engineers to translate AI-generated hypotheses into tangible experiments and to troubleshoot the sim-to-real gap.
• Reporting & Communication: Clearly and efficiently report on experimental progress, findings, and challenges to the wider Material Intelligence team and key stakeholders.

About you

In order to set you up for success as a Laboratory Research Scientist at Google DeepMind, we look for the following skills and experience:

• Deep, recognized expertise in materials synthesis methodologies (e.g., solid state synthesis, thin-film deposition or combinatorial methods).
• Extensive hands-on experience and a significant track record of synthesizing and discovering novel materials in a laboratory setting,
• Strong conceptual understanding of laboratory automation, robotics, and high-throughput experimental workflows.
• Comprehensive knowledge of a wide array of material characterization and measurement techniques
• Proven experience in setting up, equipping, and commissioning new laboratory spaces or significant experimental capabilities
• Strong laboratory management skills

Required:

• PhD and post-PhD experience in Materials Science, Solid-State Chemistry, Condensed Matter Physics, or a related field.
• Deep, recognized expertise and extensive hands-on experience in solid-state synthesis methodologies.
• Proven, hands-on proficiency with a wide array of material characterization and property measurement techniques (e.g., Powder XRD, SEM/EDS, thermal analysis, relevant electrical/magnetic property measurements).
• Proven experience in setting up, equipping, and commissioning new laboratory spaces or significant experimental capabilities.
• Demonstrated ability to independently lead and manage complex experimental research projects, from conception to data analysis and publication/patenting.
• High attention to detail and a history of persistence in troubleshooting complex experimental challenges to produce high-quality data.
• Excellent teamwork and communication skills, with experience in interdisciplinary collaboration between experimental and computational/theory groups.

In addition, the following would be an advantage: 

• Expertise in one or more advanced synthesis techniques (e.g., thin-film deposition (PVD/CVD), combinatorial methods, high-pressure synthesis).
• Strong conceptual and/or practical experience with laboratory automation, robotics, and high-throughput experimental workflows.
• Experience in laboratory management, including budgeting, procurement, and ensuring compliance with health & safety requirements.
• Excellent lab operations and stakeholder management, including experience managing external relationships with vendors, equipment suppliers and contractors.
• A significant track record of high-impact research in materials science or related areas.
• Experience hiring and mentoring junior researchers.
• Familiarity with programming (e.g., Python) for instrument control or custom data analysis.

Application deadline: Tuesday 22nd July. 

At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know