Postdoctoral Research Associate, AI/ML for Chemical Reactions and Automation

UT-Battelle; Oak Ridge (TN); On-site; USD 70,000 - 90,000; Full time

Benefits offered by this job

Health insurance

Retirement plan

Relocation assistance

Flexible work hours

Job summary

UT-Battelle/ORNL seeks a Postdoctoral Research Associate to advance AI/ML methods for understanding and guiding chemical reactions. The role combines spectroscopy data and molecular simulations to build predictive models and guide new experiments using Bayesian optimization and active learning.

The successful candidate will develop automated workflows, model training, and experimental recommendations in close collaboration with experimental and computational researchers at Oak Ridge National

Qualifications

• Ph.D. in chemical engineering, chemistry, computer science, applied mathematics, physics, or a related field.
• Experience with Python, C, and/or C++ applied programming.
• Proficiency in programming and simulation tools such as Python, C, C++, and/or ML frameworks (Scikit-learn, Keras, TensorFlow, PyTorch).
• Ability to work with experimental and computational researchers and communicate results clearly.

Responsibilities

• Develop and apply deep learning multimodal AI/ML models that combine spectroscopy data, molecular structures, reaction conditions, and simulation results to understand chemical reactions and guide new experiments.
• Prepare and organize experimental and computational datasets, including data cleaning, spectral preprocessing, quality checks, and consistent recording of experimental conditions.
• Develop Bayesian optimization and active learning methods to recommend new experimental conditions.
• Develop and demonstrate an automation pipeline that processes new data, retrain models, and recommend the experiments.
• Maintain reproducible code and workflows, communicate results to the project team, and contribute to publications, presentations, and project reports.

Skills

Python

C

C++

ML frameworks

Data analysis

Communication

Education

PhD in a related field

Tools

HPC

GPU computing

Job description

Overview

We are seeking a Postdoctoral Research Associate who will focus on the development and application of artificial intelligence and machine learning (AI/ML) methods to understand and guide chemical reactions. The research will combine experimental spectroscopy data and molecular simulations to develop predictive models, estimate prediction uncertainty, and guide the selection of new experiments using Bayesian optimization and active learning. The successful candidate will also develop and demonstrate an automated workflow, model training, and experimental recommendations in close collaboration with experimental and computational researchers. This position resides in the Center for Molecular Biophysics (CMB), Biosciences Division (BSD) at Oak Ridge National Laboratory (ORNL).

Requisition Id 17428

Overview

We are seeking a Postdoctoral Research Associate who will focus on the development and application of artificial intelligence and machine learning (AI/ML) methods to understand and guide chemical reactions. The research will combine experimental spectroscopy data and molecular simulations to develop predictive models, estimate prediction uncertainty, and guide the selection of new experiments using Bayesian optimization and active learning. The successful candidate will also develop and demonstrate an automated workflow, model training, and experimental recommendations in close collaboration with experimental and computational researchers. This position resides in the Center for Molecular Biophysics (CMB), Biosciences Division (BSD) at Oak Ridge National Laboratory (ORNL).

Major Duties/Responsibilities

• Develop and apply deep learning multimodal AI/ML models that combine spectroscopy data, molecular structures, reaction conditions, and simulation results to understand chemical reactions and guide new experiments.
• Prepare and organize experimental and computational datasets, including data cleaning, spectral preprocessing, quality checks, and consistent recording of experimental conditions.
• Develop Bayesian optimization and active learning methods to recommend new experimental conditions.
• Develop and demonstrate an automation pipeline that processes new data, retrain models, and recommend the experiments. Work with the experimental team to connect this pipeline with laboratory software and instruments where feasible.
• Maintain reproducible code and workflows, communicate results to the project team, and contribute to publications, presentations, and project reports.

Basic Qualifications

• A Ph.D. in chemical engineering, chemistry, computer science, applied mathematics, physics, or a related field.
• Experience with Python, C, and/or C++ applied programming.
• Proficiency in programming and simulation tools such as Python, C, C++, and/or ML frameworks (Scikit-learn, Keras, TensorFlow, PyTorch).
• Ability to work with experimental and computational researchers and communicate results clearly.
• Strong analytical and problem-solving skills, with the ability to work independently on complex research problems.

Preferred Qualifications

• Strong background in applying machine learning and deep learning methods to chemistry, molecular properties, chemical reactions, spectroscopy, or related scientific problems.
• Experience with Bayesian optimization, active learning, and Gaussian process model, particularly for problems with limited experimental data.
• Experience building automated scientific workflows, including data ingestion, model training, prediction, and tracking of experimental results.
• Familiarity with molecular simulations, quantum chemistry, or reaction kinetics and the use of computational results in machine learning.
• Experience using high-performance computing (HPC), parallel job submission scripts, software repository tools.
• Excellent written and oral communication skills.
• Track record of publishing research results in peer-reviewed scientific journals and presenting research at scientific conferences.
• Motivated self-starter with the ability to work independently and to participate creatively in collaborative teams across the laboratory.

Special Requirements

Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting their appointment. The appointment length will be up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and availability of funding.

• For employment at Oak Ridge National Laboratory (ORNL), a Real ID compliant form of identification will be required. Additionally, ORNL is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as mandated by Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which requires a favorable post-employment background investigation.
• To obtain this credential, new employees must successfully complete and pass a Federal Tier 1 background check investigation. This investigation includes a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last year. This includes marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws
• For foreign national candidates: If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) risk determination to maintain employment. Once you meet the three-year residency requirement, you will be required to obtain a PIV credential to maintain employment.

About ORNL

As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation’s most pressing challenges. Our team is made up of over 7,000 dedicated and innovative individuals! Our goal is to create an environment where a variety of perspectives and backgrounds are valued, ensuring ORNL is known as a top choice for employment. These principles are essential for supporting our broader mission to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security challenges facing the nation.

ORNL offers competitive pay and benefits programs to attract and retain individuals who demonstrate exceptional work behaviors.

The laboratory provides a range of employee benefits, including medical and retirement plans and flexible work hours, to support the well-being of you and your family.

Employee amenities such as on-site fitness, banking, and cafeteria facilities are also available for added convenience.

Other benefits include the following:

• Prescription Drug Plan
• Dental Plan
• Vision Plan
• 401(k) Retirement Plan
• Contributory Pension Plan
• Life Insurance
• Disability Benefits
• Generous Vacation and Holidays
• Parental Leave
• Legal Insurance with Identity Theft Protection
• Employee Assistance Plan
• Flexible Spending Accounts
• Health Savings Accounts
• Wellness Programs
• Educational Assistance
• Relocation Assistance
• Employee Discounts

This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.

We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment.

ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply. UT-Battelle is an E-Verify employer.