AI-Enabled Catalyst Discovery Postdoctoral Researcher

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 hiring a postdoctoral researcher in Chemical Engineering, Materials Science, Computer Science, Data Science, Applied Mathematics or closely related field to support our Integrated Energy Technologies Department. The postdoctoral researcher will lead the development of an artificial intelligence (AI)-enabled catalyst discovery workflow that integrates experimental data, mechanistic understanding, and machine learning to accelerate heterogeneous catalyst development for propane dehydrogenation. This position lies at the interface of catalysis, data science, and scientific software development, supporting the creation of a closed loop experimental and computational platform for autonomous catalyst optimization.

Idaho National Laboratory is hiring a postdoctoral researcher in Chemical Engineering, Materials Science, Computer Science, Data Science, Applied Mathematics or closely related field to support our Integrated Energy Technologies Department. The postdoctoral researcher will lead the development of an artificial intelligence (AI)-enabled catalyst discovery workflow that integrates experimental data, mechanistic understanding, and machine learning to accelerate heterogeneous catalyst development for propane dehydrogenation. This position lies at the interface of catalysis, data science, and scientific software development, supporting the creation of a closed loop experimental and computational platform for autonomous catalyst optimization.

Our team works a 9x80 schedule located out of our Idaho Falls facility with every other Friday off.

Primary Responsibilities Include

• Design, develop, and maintain machine learning workflows for catalyst performance prediction and inverse catalyst design.
• Develop forward predictive models that relate catalyst synthesis parameters, physiochemical characterization, and transient kinetic descriptors to catalytic performance metrics including yield, selectivity, and stability.
• Implement inverse-design algorithms that recommend new catalyst compositions and synthesis conditions for experimental validation.
• Integrate heterogeneous datasets generated from high-throughput synthesis, catalyst screening, transient kinetic measurements, and reactor scale testing into a unified data pipeline.
• Develop automated data preprocessing, feature engineering, uncertainty quantification, model validation, and candidate-ranking workflows.
• Interface machine learning models with the project’s graph-based ontology and FAIR data infrastructure to enable automated model training and data ingestion.
• Collaborate closely with catalyst synthesis, high-throughput screening, transient kinetics, and reactor testing teams to incorporate newly generated experimental data into iterative model refinement.
• Evaluate model performance using statistical cross-validation and experimental validation across catalyst development scales, from research powders through technical catalyst forms.
• Develop reproducible software, documentation, and visualization tools that support workflow deployment and long-term maintainability.
• Contribute to publications, technical reports, software releases, presentations, and project reviews.

Required

• PhD in Chemical Engineering, Material Science, Computer Science, Data Science, Applied Mathematics, or a closely related field.
• PhD requirements must be completed by commencement of appointment and within the previous 5 years.
• Experience developing machine learning models using Python and scientific computing libraries (e.g., PyTorch, TensorFlow, scikit-learn).
• Experience with scientific data analysis, statistical learning, and predictive modeling.
• Strong programming skills and experience with software version control.
• Demonstrated ability to work in multidisciplinary research teams.

The Ideal Candidate Will Possess

• Experience applying machine learning to chemistry, catalysis, material science, or reaction engineering.
• Familiarity with Bayesian optimization, active learning, inverse design, or uncertainty quantification.
• Experience with graph databases, knowledge graphs, or ontology development.
• Experience developing scientific workflows for automated or high-throughput experimentation.
• Knowledge of heterogeneous catalysis, reaction kinetics, or catalyst characterization techniques.
• Experience with cloud computing, workflow orchestration, or containerized software environments.

Physical Requirements

While performing the duties of this classification, the employee is frequently required to stand, walk, sit, stoop, bend, and work in an office and laboratory environment. The job requires hand/finger dexterity to keyboard or type, handle materials, manipulate tools, and reach with hands and arms. The job requires operation of job-related equipment. The employee must occasionally lift and/or move up to 25 pounds without assistance. Sufficient visual acuity and hearing capacity to perform the essential functions and interact with the people is required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Job Information

• The pay for this position is $105,144.00 Annually. At Idaho National Laboratory compensation decisions are determined using factors such as education, relevant experience, and other credentials.

About Us

Benefits and Relocation

• Medical, Dental, Vision, and Flexible Spending Accounts
• 401(k) with a 4.2% employer contribution and up to 4.8% match (regular positions) or self-contribute access (postdoctoral positions)
• Paid time off (personal leave)
• Employee Education Program (tuition assistance for eligible positions)
• Comprehensive Relocation Package
• Benefit eligibility subject to multiple factors, including employment status and position classification.

At this time, BEA will not sponsor any H1-B visas obtained outside of the United States of America (U.S.A.), including consular visas.

INL Mission

Our mission is to discover, demonstrate and secure innovative nuclear energy solutions, other clean energy options and critical infrastructure.

INL Vision

Our vision is to change the world's energy future and secure our nation's critical infrastructure.

Selective Service Requirements

To be eligible for employment at INL males born after December 31, 1959 must have registered with the Selective Service System (SSS). For more information see www.sss.gov .

Equal Employment Opportunity

Idaho National Laboratory (INL) is an Equal Employment Opportunity (EEO) employer. It is the policy of INL to provide equal employment opportunities to all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information.

Reasonable Accommodation

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.