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Postdoctoral In Reinforcement Learning Jobs in Tennessee

Relativity

Principal Applied Scientist

Nashville, TN · On-site +1

$134K - $202K/yr

... in this position. Required Skills Algorithms, Data Analysis, Machine Learning (ML), Natural Language, Python (Programming Language), Reinforcement Learning, Researching, Scientific Writing ...

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Postdoctoral In Reinforcement Learning information

What is the difference between Postdoctoral In Reinforcement Learning vs Postdoctoral In Machine Learning?

AspectPostdoctoral In Reinforcement LearningPostdoctoral In Machine Learning
Required CredentialsPhD in Computer Science, AI, or related field; strong programming skills; research experience in reinforcement learningPhD in Computer Science, AI, or related field; strong programming skills; research experience in machine learning
Work EnvironmentAcademic labs, research institutions, industry R&D teams focused on reinforcement learning applicationsAcademic labs, research institutions, industry R&D teams working on various machine learning techniques
Industry UsagePrimarily in AI research, robotics, gaming, and autonomous systemsBroader applications including data analysis, predictive modeling, and AI research

Postdoctoral In Reinforcement Learning specializes in research related to decision-making algorithms and autonomous systems, whereas Postdoctoral In Machine Learning covers a wider range of AI techniques. Both roles require similar credentials but differ in focus and application areas.

What are the key skills and qualifications needed to thrive as a Postdoctoral Researcher in Reinforcement Learning, and why are they important?

To thrive as a Postdoctoral Researcher in Reinforcement Learning, you need a PhD in computer science or a related field, with deep expertise in machine learning, statistics, and algorithm development. Proficiency in programming languages such as Python, experience with deep learning frameworks (e.g., TensorFlow or PyTorch), and familiarity with reinforcement learning libraries are typically required. Strong analytical thinking, problem-solving ability, collaboration, and scientific communication skills help you excel in research teams and publish impactful work. These competencies are vital to advancing state-of-the-art research, developing novel algorithms, and contributing to the academic and industrial progress in AI.

What are some common challenges faced by postdoctoral researchers in reinforcement learning, and how can they be addressed?

Postdoctoral researchers in reinforcement learning often face challenges such as balancing independent research projects with collaborative work, staying up-to-date with rapidly evolving literature, and managing the pressure to publish in top conferences. Effective time management, regular engagement with the research community through seminars and workshops, and seeking mentorship from senior colleagues can help address these challenges. Additionally, collaborating with interdisciplinary teams can offer fresh perspectives and support, making it easier to navigate complex research problems.

What is a Postdoctoral Researcher in Reinforcement Learning?

A Postdoctoral Researcher in Reinforcement Learning is an individual who has completed a PhD and conducts advanced research in the field of reinforcement learning, a branch of artificial intelligence focused on how agents take actions in environments to maximize rewards. These researchers often work in academic, industrial, or governmental research settings, collaborating on projects that advance the theoretical foundations or practical applications of reinforcement learning. Their responsibilities may include designing experiments, developing algorithms, publishing papers, and mentoring graduate students.
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Infographic showing various Postdoctoral In Reinforcement Learning job openings in Tennessee as of July 2026, with employment types broken down into 1% As Needed, 74% Full Time, 18% Part Time, 2% Temporary, and 5% Contract. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution.
Postdoctoral Research Associate - AI Models for Power Grid System

Postdoctoral Research Associate - AI Models for Power Grid System

Oak Ridge National Laboratory

Oak Ridge, TN

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 21 days ago

Oak Ridge National Laboratory rating

8.8

Company rating: 8.8 out of 10

Based on 16 frontline employees who took The Breakroom Quiz

10th of 105 rated laboratories

Job description

Requisition Id 16687 

Overview:

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.

The Computational Coupled Physics (CCP) Group within the Computational Sciences and Engineering Division (CSED), at Oak Ridge National Laboratory (ORNL) is seeking a Postdoctoral Research Associate to develop, scale, and apply artificial intelligence (AI) and deep learning (DL) models for power grid systems. The successful candidate will contribute to scalable AI workflows for grid modeling, optimal power flow (OPF), surrogate modeling, and data-driven analysis of large-scale electric power system simulations on DOE leadership-class computing resources. The candidate is expected to bring strong expertise in scalable deep learning, high-performance computing (HPC), scalable data management, Linux environments, and production-quality scripting for HPC workflows.

Major Duties/Responsibilities:

  • Participate in the design, implementation, and deployment of scalable AI/DL models for power grid systems, including surrogate models and foundation-model workflows for OPF and related grid simulation tasks.
  • Develop and maintain HPC-ready software workflows for distributed training, large-scale inference, scalable data ingestion, and data management on leadership-class computing systems and institutional clusters.
  • Write robust Linux bash scripts and job submission scripts for SLURM and PBS environments, including multi-node GPU/CPU workflows, monitoring, restart, and post-processing pipelines.
  • Author peer reviewed papers for journals and conferences, technical reports, open-source software, and represent the organization by making technical presentations at workshops and conferences.
  • Collaborate within a multi-disciplinary research environment consisting of computational scientists, computer scientists, electrical engineers, domain scientists, and applied mathematicians conducting basic and applied AI/DL research in support of the Laboratory’s missions.

Basic Qualifications:

  • A PhD in computer science or an AI-related field completed within the last 5 years.
  • Demonstrated expertise in scalable deep learning, including distributed training and/or large-scale inference using modern AI frameworks such as PyTorch.
  • Demonstrated experience with high-performance computing systems, including multi-node workflows on CPU and/or GPU clusters.
  • Demonstrated expertise in scalable data management for AI/ML workflows, including efficient data preprocessing, storage, streaming, and I/O for large scientific datasets.
  • Demonstrated experience writing SLURM and PBS job submission scripts for HPC clusters, including batch workflows, job arrays, environment setup, and restart logic.
  • Demonstrated expertise with the Linux operating system, bash scripting, Git, Python, and reproducible software environments.
  • Demonstrated expertise in writing advanced software in Python and in the design and implementation of deep learning algorithms.
  • Expertise in object-oriented programming, scripting languages, and modern software engineering practices for research codes.
  • Demonstrated effective written and oral communication skills, a proven publication record, and effective interpersonal skills.

Preferred Qualifications:

  • Knowledge of graph neural networks and other geometric deep learning approaches for graph-structured scientific or engineering data.
  • Background in electrical engineering, power systems, grid modeling, or power system optimization.
  • Experience with optimal power flow and grid simulation solvers or toolchains, such as MATPOWER, PSS/E, PowerModels, or related open-source or commercial packages.
  • Experience working in a multi-disciplinary research environment that follows modern software quality standards, including version control, unit testing, documentation, and continuous integration.
  • Motivated self-starter with the ability to work independently, participate creatively in collaborative teams, function well in a fast-paced research environment, and adapt to evolving project needs.

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 for up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and the availability of funding.

Candidates are asked to submit a detailed cover letter describing their experience relative to the duties and qualifications described in this posting with their application.

Please submit three letters of reference when applying to this position. You can upload these directly to your application or have them sent to postdocrecruitment@ornl.gov with the position title and number referenced in the subject line.

Instructions to upload documents to your candidate profile:

  • Login to your account via jobs.ornl.gov
  • View Profile
  • Under the My Documents section, select Add a Document

Technical questions:

Massimiliano Lupo Pasini (lupopasinim@ornl.gov), Alex Plotkowski (plotkowskiaj@ornl.gov)

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, and 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.

If you have trouble applying for a position, please email ORNLRecruiting@ornl.gov.

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.

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