Postdoctoral Research Associate - AI Catalysis
Core
Designing and conducting experimental heterogeneous-catalysis research within autonomous, closed-loop laboratory workflows to accelerate the discovery of catalytic materials for energy and sustainability applications.
Role type
Postdoctoral Research Associate (AI Catalysis)
Builds
Scholarly publications, sponsored-research deliverables, and autonomous laboratory workflows
Domain
Chemical Engineering / Materials Science / Machine Learning
Deliverable
production ML models | physical/clinical work
Required skills
Heterogeneous catalysis, reaction kinetics, thermodynamics, structure–reactivity relationships, catalytic reactor operation, catalyst synthesis and characterization, Python programming, machine learning for scientific data
Preferred skills
None stated
Technologies
Python, active-learning, Bayesian-optimization pipelines
Responsibilities
Design, synthesize, and test heterogeneous catalysts and operate catalytic reactors to measure activity, selectivity, and kinetics; Develop and run closed-loop autonomous workflows coupling automated synthesis, high-throughput screening, and online/in situ characterization with active-learning and Bayesian-optimization pipelines; Build agentic artificial intelligence (AI) workflows and FAIR experimental data infrastructure for instrument orchestration, automated data curation, and autonomous hypothesis generation; Analyze experimental and characterization data to extract structure–reactivity relationships and connect empirical findings to mechanistic and kinetic interpretation; Disseminate results through peer-reviewed publications and presentations, contribute to proposals and reports, and help mentor graduate and undergraduate researchers
Seniority
Postdoctoral Researcher