Automation Scientist

Caltech is a world-renowned science and engineering institute that marshals some of the world's brightest minds and most innovative tools to address fundamental scientific questions. We thrive on finding and cultivating talented people who are passionate about what they do. Join us and be a part of the diverse Caltech community.

Caltech has been awarded funding under the National Science Foundation's Programmable Cloud Laboratories (PCL) Test Bed program to establish ELECTRA, a remotely accessible, AI-enabled automated laboratory for electron diffraction (MicroED) and structural elucidation. ELECTRA is one node in a planned nationwide network of PCL Test Bed facilities that will let researchers anywhere, including at institutions with limited access to advanced instrumentation, submit and run real experiments over the cloud. We are hiring the founding team that will help build and operate the node. The cross-disciplinary team is composed of scientists and engineers from academia and the private sector. This project will directly impact various scientific fields, including chemistry, biology, and materials science, with applications in tech and medicine. (See https://www.nsf.gov/tip/updates/nsf-announces-400m-investment-new-national-network-ai.)

As Automation Scientist, you will design the scientific logic behind ELECTRA's automated experiments, from electron microscopy and sample-prep workflows to the acceptance criteria that make a remotely run experiment trustworthy, and support the users who run them.

• Design, build, and validate automated and semi-autonomous electron microscopy and sample-preparation workflows, including closed-loop, active-learning strategies that improve hit rates with less human intervention.
• Express experimental logic as reviewable protocols and machine-readable specifications, and establish the acceptance criteria, calibration routines, validation standards, and failure/recovery definitions that make a remotely executed experiment trustworthy.
• Analyze and interpret experimental datasets, and curate high-quality datasets, including metadata and failure cases, to inform workflow design and support AI-driven experiment design and cross-node standards.
• Collaborate with the team to translate experimental logic into instrument-control routines, scheduling constraints, and user-facing interfaces, and co-develop common experimental-design and laboratory protocols with counterparts at other PCL nodes.
• Provide expert technical support to onboarded users, on-site and remote, helping them translate scientific questions into executable ELECTRA experiments.
• Contribute to recruitment and onboarding workshops, user documentation, and facility tours; mentor students and junior staff; and contribute to publications and technical reports.

• Ph.D. in chemistry, materials science, structural biology, chemical engineering, physics, or a related field plus 1 year of related experience (or Master's Degree with at least 3 years of related experience).
• Track record of publishing work.
• Hands-on experience with a structural characterization method.
• Experience automating laboratory workflows or running high-throughput experimentation.
• Proficiency in coding and data processing.
• Strong collaboration and written communication skills, and genuine interest in supporting users at institutions with fewer resources than ours.

• Electron diffraction experience, including low-dose data collection and sample preparation.
• Experience with self-driving labs, materials acceleration platforms, active learning, or Bayesian experimental design.
• Fluency with crystallography pipelines (XDS, DIALS, CCP4, PHENIX, SHELX, or equivalents).
• Robotic sample handling or liquid-handling automation.
• Experience supporting external users at a shared instrument facility, beamline, or core.

• Resume
• Cover letter explaining relevant experience