Minimum qualifications:
- PhD in Physics, Materials Science, or Electrical Engineering, or a related field.
- 5 years of experience with thin-film synthesis methods (e.g., PVD, Sputtering, (MO)CVD, ALD, MBE, or PLD) and experience optimizing multi-element chemistries.
- Experience in characterizing thin films and interfaces, particularly GI-XRD, SEM/EDX, XPS, AFM, Raman/FTIR, ellipsometry, etc.
Preferred qualifications:
- PhD degree.
- Experience with laboratory automation, robotics, or high-throughput experimental workflows, and in a materials R&D lab.
- Experience probing electronic, mechanical, thermal, optical, magnetic, and other properties of functional thin films using a wide range of characterization techniques.
- Experience with lab management software or managing chemical inventories and safety documentation.
- Experience with programming (e.g., Python) for instrument control or custom data analysis and understanding of computational methods and foundational models.
- Understanding of lab operations, instrument health, and safety. stringent safety protocols, regarding vacuum systems, high-voltage equipment, and the safe handling of hazardous chemical precursors.
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 our toolkit to accelerate scientific discovery. By bringing together specialists with backgrounds in machine learning, computer science, physics, chemistry, biology and more, we are 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 the materials research program, combining high-throughput synthesis and characterization with advanced robotics to create a closed-loop discovery system.
In this role, you will build the experimental foundation for autonomous discovery loops, utilizing advanced deposition platforms to realize novel thin-film materials predicted by the AI. You will collaborate with computational scientists to bridge the gap between sim and real, and partner with engineers to design the next generation of automated library generation and screening infrastructure.
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.
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
- Develop and execute thin-film synthesis strategies using deposition techniques like PVD, Sputtering, MOCVD, PLD, and ALD to create combinatorial materials libraries.
- Lead the structural and chemical validation of these libraries using techniques like XRD, SEM, AFM, Raman, and ellipsometry, ensure excellent quality control of crystal phase and film thickness.
- Partner with a wider material intelligence team to build predictive models of growth dynamics, analyze how deposition recipes correlate with functional properties.
- Work with automation engineers to integrate deposition tools with high-throughput metrology, design closed-loop workflows that can screen thousands of compositions on a single wafer.
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also
Google's EEO Policy and
EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our
Accommodations for Applicants form.
