Posted 2 months ago
Postdoctoral Research Associate - AI Catalysis
AI Summary
Designs and conducts experimental heterogeneous-catalysis research within autonomous, closed-loop laboratory workflows, integrating catalyst synthesis, high-throughput reactor testing, and in situ characterization with machine-learning and agentic AI methods to accelerate catalytic materials discovery.
About this role
About the Opportunity
Job Summary
Under the direction of the Principal Investigator, the Postdoctoral Research Associate designs and conducts experimental heterogeneous-catalysis research within autonomous, closed-loop (“self-driving”) laboratory workflows. The role integrates catalyst synthesis, high-throughput reactor testing, and in situ/operando characterization with machine-learning and agentic artificial intelligence (AI) methods that propose, prioritize, and interpret experiments, accelerating the discovery and optimization of catalytic materials for energy and sustainability applications. The position contributes to scholarly publications, sponsored-research deliverables, and the training of graduate and undergraduate researchers.
Minimum Qualifications
Required
- PhD in Chemical Engineering, Chemistry, Materials Science, or a closely related field
- Knowledge of heterogeneous catalysis, reaction kinetics, thermodynamics, and structure–reactivity relationships
- Ability to design and operate catalytic reactors
- Ability to synthesize and characterize catalysts
- Proficiency in Python programming
- Ability to apply machine-learning methods to scientific data
- Ability to work independently and across disciplines
Key Responsibilities & Accountabilities
- Design, synthesize, and test heterogeneous catalysts (e.g., supported metals, oxides, single-atom systems, and high-entropy metal alloy systems) and operate catalytic reactors to measure activity, selectivity, and kinetics for targeted thermo- and/or electrocatalytic reactions
- Develop and run closed-loop autonomous workflows that couple automated synthesis, high-throughput screening, and online/in situ characterization with active-learning and Bayesian-optimization pipelines to guide experiment selection
- Build agentic artificial intelligence (AI) workflows and FAIR experimental data infrastructure for instrument orchestration, automated data curation, and autonomous hypothesis generation linking synthesis, characterization, and performance
- 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 and steward shared instrumentation
Required Documents
- Resume
Position Type
ResearchAdditional Information
Northeastern University considers factors such as candidate work experience, education and skills when extending an offer.
Northeastern has a comprehensive benefits package for benefit eligible employees. This includes medical, vision, dental, paid time off, tuition assistance, wellness & life, retirement- as well as commuting & transportation. Visit https://hr.northeastern.edu/benefits/ for more information.
All qualified applicants are encouraged to apply and will receive consideration for employment without regard to race, religion, color, national origin, age, sex, sexual orientation, disability status, or any other characteristic protected by applicable law.
Compensation Grade/Pay Type:
108SExpected Hiring Range:
$60,315.00 - $85,192.50With the pay range(s) shown above, the starting salary will depend on several factors, which may include your education, experience, location, knowledge and expertise, and skills as well as a pay comparison to similarly-situated employees already in the role. Salary ranges are reviewed regularly and are subject to change.
Skills
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