Materials Artificial Intelligence and Automation Research Engineer
The High Throughput Experimentation (HTE) group at Caltech is ushering in a new paradigm of materials science research through the development and deployment of new experimental techniques coupled with Artificial Intelligence (AI). Through projects funded by NSF, DOE, DOD, and industry, a suite of strategies for accelerating scientific discovery are being adapted for specific research goals, resulting in an ever-expanding toolbox of experimental and computational techniques. The group has a strong history of experiment automation, and as AI algorithms motivate new modes of automation, technique development proceeds accordingly. The successful candidate will contribute to software development for automating experiments as well as integration of AI methods in research workflows. While the group applies established machine learning algorithms where appropriate, many projects focus on identifying the most challenging data science problems and working with computer scientists to solve them with next-generation AI algorithms, as described in a recent Perspective (https://doi.org/10.1557/mrs.2019.158).
HTE team members work in a highly collaborative environment including engineers and experimentalists who interact with theorists and computer scientists to adopt and advance the integration of theory and AI in experimental investigations. The Materials AI and Automation Research Engineer will work on a variety of research projects involving discovery of new solid state materials (mostly in thin film form) that are critical to new and emerging energy technologies. The team seeks an engineer with deep expertise in both materials scientist and the incorporation of computational methods into materials discovery. Specific training in AI methods is not a requirement provided sufficient expertise in mathematics and computer programming. In the cover letter, applicants should clearly demonstrate their technical aptitude, critical thinking, passion for discovery, and appreciation for team science. The successful candidate will work in the lab at Caltech and will report directly to the principal investigator of the HTE group.
- Work with the engineering team to integrate computational techniques with high throughput experiments.
- Work closely with the pipeline development team to construct, implement, and commission data management and processing systems to tighten the feedback loop between experiments and data interpretation.
- Fabricate and operate high throughput experimental pipelines for synthesis, screening, and characterization of (photo)electrocatalyst libraries with focus on materials discovery.
- Design and program algorithms for analysis of datasets produced by high throughput experimental pipelines.
- Participate in team effort to design, synthesize, screen, characterize, and understand (photo)electrocatalysts for solar fuels applications.
- Publish research results in peer-review journals.
- Bachelors degree in Materials Science, Physics, Chemistry, Computer Science or related field.
- 1 year experience with development or use of computational methods in the physical sciences.
- 2 years experience with materials discovery research.
- 1 year experience with development of data analysis algorithms.
- Excellent communication skills to work effectively with scientists, engineers, and technicians in a team-oriented environment.
- PhD in Materials Science, Physics, Chemistry, Computer Science or related field.
- 2+ years experience with development and use of AI techniques.
- 4+ years experience in thin film materials synthesis and characterization.
- 2+ years experience with development of data analysis in the Python programming language.
- 2+ years experience with software development for experiment automation.
- Cover Letter