AI Catalyst Discovery Postdoc (9x80 Schedule)

Idaho National Laboratory; Idaho Falls (ID); On-site; USD 94,629 - 115,658; Full time

Benefits offered by this job

Medical, Dental, Vision

401(k) with employer contribution

Tuition assistance

Relocation Package

Paid time off

Flexible Spending Accounts

Job summary

Idaho National Laboratory is seeking a postdoctoral researcher to lead an AI-enabled catalyst discovery workflow, integrating experimental data, mechanistic understanding, and machine learning to accelerate propane dehydrogenation catalysts.

The role sits at the interface of catalysis, data science, and software development, enabling a closed-loop platform for autonomous catalyst optimization. Ideal candidates have PhDs and a strong ML, data analysis, and programming background.

Qualifications

• PhD completed by appointment start and within last 5 years.
• Experience building ML models with Python and scientific libraries (PyTorch, TensorFlow, scikit-learn).
• Experience with scientific data analysis, statistics, and predictive modeling.
• Strong programming skills and version control experience.
• Ability to work in multidisciplinary research teams.

Responsibilities

• Design, develop, and maintain ML workflows for catalyst performance prediction and inverse design.
• Develop forward models linking synthesis, characterization, and kinetics to performance metrics.
• Implement inverse-design algorithms for experimental validation of new catalysts.
• Integrate heterogeneous datasets into a unified data pipeline.
• Develop automated data preprocessing, feature engineering, uncertainty quantification, model validation, and candidate ranking workflows.
• Interface ML models with graph-based ontology and FAIR data infrastructure.
• Collaborate with synthesis, high-throughput screening, kinetics, and reactor teams to feed new data into models.
• Evaluate model performance via cross-validation and experimental validation across scales.
• Develop reproducible software, documentation, and visualization tools.
• Contribute to publications, technical reports, software releases, and reviews.

Skills

Python

Machine Learning

PyTorch

TensorFlow

scikit-learn

Data Analysis

Multidisciplinary Teamwork

Cloud Computing

Git

Containerized Environments

Education

PhD in Chemical Engineering

PhD in Materials Science

PhD in Computer Science

PhD in Data Science

PhD in Applied Mathematics

PhD in related field

Tools

Git

Containerization

Job description

Idaho National Laboratory is seeking a postdoctoral researcher to lead an AI-enabled catalyst discovery workflow, integrating experimental data, mechanistic understanding, and machine learning to accelerate propane dehydrogenation catalysts.

The role sits at the interface of catalysis, data science, and software development, enabling a closed-loop platform for autonomous catalyst optimization. Ideal candidates have PhDs and a strong ML, data analysis, and programming background.