Post Doctoral Researcher, Center for Clean Hydrogen

Pay Grade: 90E Context of Job: The Postdoctoral Researcher will develop automated workflows integrating artificial intelligence and machine learning (AI/ML) for the Center for Clean Hydrogen’s AEM Moonshot project. The project combines AI/ML, molecular simulation, and automated, self-driving laboratories to discover anion exchange membranes (AEMs) with improved hydroxide conductivity and chemical durability.

Working with collaborators with expertise in polymer chemistry, computation, and membrane characterization, the researcher will connect laboratory automation with predictive models and intelligent experiment selection to build a closed-loop discovery platform that coordinates experiments, captures and analyzes measurements, and uses results to improve models and guide subsequent experiments.

Major Responsibilities: Develop automated experimental workflows, including instrument integration, data acquisition, and analysis. Integrate AI/ML models with experiments to predict material properties and guide candidate selection through active learning and uncertainty-informed decision-making. Build reproducible data pipelines connecting experimental measurements, computational results, and shared project datasets.

Collaborate with project partners to validate predictions and investigate relationships among polymer chemistry, structure, conductivity, and stability. Work with project partners to scale up promising candidates to deployable devices. Maintain experimental records, document software and laboratory protocols, and prepare manuscripts for publication.

Ensure proper use and maintenance of laboratory equipment, support student researchers, and follow applicable laboratory safety procedures.

Qualifications

Applicants should hold a PhD by the start date in chemical engineering, materials science, chemistry, electrical engineering, mechanical engineering, computer science, or a related field. Relevant experience is welcomed in one or more of the following areas: Programming, particularly Python; laboratory automation; scientific instrumentation control; or AI/ML for scientific applications.

Robotics, active learning, Bayesian optimization, molecular representations, or scientific data infrastructure. Polymers, membranes, or electrochemical characterization and analysis. Environmental/Occupational Exposures: Laboratory work may involve chemicals and materials used in membrane preparation and characterization, as well as automated and electrochemical equipment.

Personal protective equipment is required as appropriate to the experimental work and applicable laboratory safety procedures. Special Requirements: Laboratory tasks require careful handling of instruments and research materials in accordance with established procedures. Work schedules may occasionally include evenings or weekends, depending on experimental timing.

With or without assistance, must be able to lift up to 20 lbs to assemble components of automation equipment.