Materials Laboratory Scientist, Solid State Synthesis, DeepMind
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Minimum qualifications:
- PhD in Materials Science, State Chemistry, Condensed Matter Physics, or in a related field, or equivalent practical experience.
- 2 years of experience in solid-state synthesis methodologies and structural characterization techniques (e.g., XRD).
Preferred qualifications:
- Experience working in laboratory automation, robotics, or high-throughput experimental workflows, in a materials R&D lab and in characterization techniques (e.g., electrical, magnetic, or optical property measurements).
- Experience in solid-state synthesis methodologies and handling air-sensitive materials in inert environments, and in structural characterization techniques, particularly XRD.
- Ability to own lab operations, instrument health, and safety, stringent laboratory safety protocols, particularly regarding vacuum systems, high-voltage equipment, and handle hazardous chemical precursors.
- Excellent programming (e.g., Python) and lab management software skills or managing chemical inventories and safety documentation skills for instrument control or custom data analysis and understanding of computational methods.
About the job
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 the 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.
Google DeepMind is establishing the Materials Discovery Laboratory, a state-of-the-art 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 bridge the gap between theoretical prediction and physical reality, developing robust synthesis strategies for superconductors, ceramics, and other functional materials. You will work at the interface of chemistry and automation, collaborating with engineers to translate bespoke bench-top techniques into standardized, high-throughput workflows that generate high-fidelity data for model training.Artificial intelligence will be one 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.
Responsibilities
- Develop and execute synthesis workflows for novel inorganic materials, using a broad range of specialty equipment.
- Lead the structural characterization of synthesized candidates using XRD and electron microscopy, applying crystallographic analysis (e.g., Rietveld refinement) to validate phase purity and atomic structure.
- Collaborate with research scientists and the wider material intelligence team to analyze experimental outcomes including negative results - to refine the predictive capabilities of our computational models.
- Partner with automation engineers to design, test, and validate new hardware modules for sample preparation and synthesis, ensuring manual recipes can be scaled into reliable robotic protocols.
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