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Oak Ridge National Laboratory
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Postdoctoral Research Associate in AI/ML for Chemical Reactions and Automation Oak Ridge National Laboratory in United States
Degree Level
Postdoc
Field of study
Computer Science
Funding
The post describes competitive pay and employee benefits, including medical and retirement plans, flexible work hours, prescription, dental and vision plans, 401(k), pension, life insurance, disability benefits, vacation and holidays, parental leave, legal insurance, employee assistance, flexible spending and health savings accounts, wellness programs, educational assistance, relocation assistance, and employee discounts. The appointment is up to 24 months, with possible extension subject to per
Country
United States
University
Oak Ridge National Laboratory
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About this position
Oak Ridge National Laboratory is seeking a Postdoctoral Research Associate in AI and machine learning for chemical reactions and automation. The position is based in the Center for Molecular Biophysics within the Biosciences Division at ORNL in Oak Ridge, Tennessee.
The researcher will develop and apply multimodal deep-learning models that integrate experimental spectroscopy, molecular structures, reaction conditions, and molecular-simulation results. The goal is to improve understanding of chemical reactions, generate predictive models with quantified uncertainty, and guide the selection of new experiments.
The project combines computational chemistry, machine learning, and experimental science. The postdoctoral researcher will prepare and organize experimental and computational datasets, perform spectral preprocessing and quality checks, and develop Bayesian-optimization and active-learning methods for recommending experimental conditions. They will also create an automated scientific workflow that processes incoming data, retrains models, generates predictions, and recommends experiments.
Close collaboration with experimental and computational researchers will support connections between the workflow, laboratory software, and instruments. The role also involves maintaining reproducible code and workflows and contributing to research publications, presentations, and project reports within ORNL’s collaborative national-laboratory environment.
Funding details
The post describes competitive pay and employee benefits, including medical and retirement plans, flexible work hours, prescription, dental and vision plans, 401(k), pension, life insurance, disability benefits, vacation and holidays, parental leave, legal insurance, employee assistance, flexible spending and health savings accounts, wellness programs, educational assistance, relocation assistance, and employee discounts. The appointment is up to 24 months, with possible extension subject to per
What's required
Applicants must hold a Ph.D. in chemical engineering, chemistry, computer science, applied mathematics, physics, or a related field, complete all degree requirements before starting, and have received the Ph.D. no more than five years before the application date. Experience with Python, C, and/or C++ programming and machine-learning frameworks is required, as is the ability to collaborate with experimental and computational researchers and communicate results clearly. Preferred qualifications include experience applying machine learning or deep learning to chemistry, molecular properties, chemical reactions, or spectroscopy; Bayesian optimization, active learning, and Gaussian-process models; automated scientific workflows; molecular simulations, quantum chemistry, or reaction kinetics; HPC; scientific software repositories; peer-reviewed publications; and conference presentations. Candidates must satisfy ORNL identification, background-investigation, DOE access, and credential requirements. Foreign-national candidates may be subject to additional residency and risk-determination requirements. Three reference letters are required.
How to apply
Apply through the ORNL Jobs portal using the advert's “Apply now” link. Submit the requested application materials and three reference letters; letters may be uploaded to the candidate profile or emailed to [email protected] with the position title and number in the subject line.
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