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Postdoctoral In Reinforcement Learning Jobs in Colorado

Staff AI/ML Engineer

Aurora, CO · On-site

$98K - $206K/yr

Experience with LLMs, Transformers, YOLO, GANs, Reinforcement Learning * Linux and AWS experience * Experience with CUDA and Python libraries such as CuPy, Numba, CuSignal, CuDF, etc. * Experience in ...

In this role, you will work with cutting-edge technologies to design, develop, and deploy machine ... Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement ...

In this role, you will work with cutting-edge technologies to design, develop, and deploy machine ... Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement ...

In this role, you will work with cutting-edge technologies to design, develop, and deploy machine ... Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement ...

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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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What job categories do people searching Postdoctoral In Reinforcement Learning jobs in Colorado look for? The top searched job categories for Postdoctoral In Reinforcement Learning jobs in Colorado are:
What cities in Colorado are hiring for Postdoctoral In Reinforcement Learning jobs? Cities in Colorado with the most Postdoctoral In Reinforcement Learning job openings:
Infographic showing various Postdoctoral In Reinforcement Learning job openings in Colorado as of June 2026, with employment types broken down into 5% Locum Tenens, 85% Full Time, 5% Part Time, and 5% Contract. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution.
Research Engineer - Machine learning applications to power system operations

Research Engineer - Machine learning applications to power system operations

The National Renewable Energy Laboratory (NREL)

Golden, CO • On-site

$76K - $126K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired today. Applications are no longer accepted.


Job description

Posting Title
Research Engineer - Machine learning applications to power system operations
Location
CO - Golden
Position Type
Regular
Hours Per Week
40
Working at NLR
NLR is located at the foothills of the Rocky Mountains in Golden, Colorado is the nation's primary laboratory for energy systems research and development.
Join the National Laboratory of the Rockies (NLR), where world-class scientists, engineers, and experts are accelerating energy innovation through breakthrough research and systems integration. From our mission to our collaborative culture, NLR stands out in the research community for its commitment to an affordable and secure energy future. Spanning foundational science to applied systems engineering and analysis, we focus on solving complex challenges to deliver advanced, secure, reliable, and cost-effective energy solutions. Our work helps strengthen U.S. industries, support job creation, and promote national economic growth.
At NLR, you'll find a mission-driven environment supported by state-of-the-art facilities, multidisciplinary research teams, and strong collaborations with industry, academia, and other national laboratories. We offer robust professional development opportunities, and a competitive benefits package designed to support your career and well-being.
Job Description
The Grid Automation and Controls Group of the Power Systems and Engineering Center (PSEC) at the National Laboratory of the Rockies (NLR) is looking for a researcher who has solid background on machine learning (ML)/artificial intelligence (AI) with enough knowledge about power systems. The candidate will work on research projects that use ML/AI to solve power system problems, specially with the focus on Large Language Models (LLM). Ideal candidate is expected to have in-depth knowledge and extensive research experience related to LLM and agentic AI. Ideal candidate should have solid programming skillset and software development experience. Knowledge and experience about power systems is a plus.
The ideal candidate should be able to conduct research work with limited guidance from senior researchers, and also collaborate with project PI and other power system researchers from the same project team.
Basic Qualifications
Relevant Master's Degree . Or, relevant Bachelor's Degree and 2 or more years of experience . General knowledge and application of engineering technical standards, principles, theories, concepts and techniques. Training in team, task or project leadership responsibilities. Intermediate abilities and knowledge of practices and techniques. Beginning experience in project management. Good writing, interpersonal and communication skills.
* Must meet educational requirements prior to employment start date.
Additional Required Qualifications
Must have a MS in computer science, electrical engineering, computer engineering or related fields. Must meet educational requirements prior to employment start date.
Additional Required Qualifications
  • Experience in natural language learning, generative AI, large language models, foundation models, etc.
  • Strong programming skill
  • Experience in using high performance computers, Linux systems

Preferred Qualifications
Preferred Qualifications
  • In-depth knowledge in graph neural networks and reinforcement learning
  • Proven records of research experience related to power systems and power system optimization
  • Have a good fundamental knowledge of neural networks, state-of-the-art learning algorithms, and their applications to complex systems
  • Proficiency in using Python and machine learning/reinforcement learning packages
  • With strong publication record

Job Application Submission Window
The anticipated closing window for application submission is up to 30 days and may be extended as needed.
Annual Salary Range (based on full-time 40 hours per week)
Job Profile: Researcher II / Annual Salary Range: $76,600 - $126,400
NLR takes into consideration a candidate's education, training, and experience, expected quality and quantity of work, required travel (if any), external market and internal value, including seniority and merit systems, and internal pay alignment when determining the salary level for potential new employees. In compliance with the Colorado Equal Pay for Equal Work Act, a potential new employee's salary history will not be used in compensation decisions.
Benefits Summary
Benefits include medical, dental, and vision insurance; short*- and long-term disability insurance; pension benefits*; 403(b) Employee Savings Plan with employer match*; life and accidental death and dismemberment (AD&D) insurance; personal time off (PTO) and sick leave; paid holidays; and tuition reimbursement*. NLR employees may be eligible for, but are not guaranteed, performance-, merit-, and achievement- based awards that include a monetary component. Some positions may be eligible for relocation expense reimbursement. Limited-term positions are not eligible for long-term disability or tuition reimbursement.
* Based on eligibility rules
Badging Requirement
NLR 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 required by Homeland Security Presidential Directive 12 (HSPD-12), which includes a favorable background investigation.
Drug Free Workplace
NLR is committed to maintaining a drug-free workplace in accordance with the federal Drug-Free Workplace Act and complies with federal laws prohibiting the possession and use of illegal drugs. Under federal law, marijuana remains an illegal drug.
If you are offered employment at NLR, you must pass a pre-employment drug test prior to commencing employment. Unless prohibited by state or local law, the pre-employment drug test will include marijuana. If you test positive on the pre-employment drug test, your offer of employment may be withdrawn.
Submission Guidelines
Please note that in order to be considered an applicant for any position at NLR you must submit an application form for each position for which you believe you are qualified. Applications are not kept on file for future positions. Please include a cover letter and resume with each position application.
Equal Opportunity Employer
All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, domestic partner status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws.
Reasonable Accommodations
E-Verify www.dhs.gov/E-Verify For information about right to work, click here for English or here for Spanish.
E-Verify is a registered trademark of the U.S. Department of Homeland Security. This business uses E-Verify in its hiring practices to achieve a lawful workforce.