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Postdoctoral In Reinforcement Learning Jobs in Colorado

Staff AI/ML Engineer

Aurora, CO · On-site

$98.50K - $206.80K/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 ...

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 ...

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Postdoctoral In Reinforcement Learning information

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.

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 popular job titles related to Postdoctoral In Reinforcement Learning jobs in Colorado? For Postdoctoral In Reinforcement Learning jobs in Colorado, the most frequently searched job titles are:
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 May 2026, with employment types broken down into 1% As Needed, and 99% Full Time. Highlights an 94% Physical, and 6% Remote job distribution.

Transportation Systems Intern (Year-Round)

Nrel

Golden, CO

$44.50K - $71.20K/yr

Part-time

Medical, Dental, Vision, Retirement

Posted 17 days ago


Job description

Posting TitleTransportation Systems Intern (Year-Round)

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LocationCO - Golden

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Position TypeIntern (Fixed Term)

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Hours Per Week20

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Working at NLRNLR 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 Advanced Computing Solutions Group in the NLR Computational Science Center has an opening for a graduate student researcher in in Transportation Systems with special emphasis on transportation system modeling and control. The researcher will assist in supporting large-scale modeling efforts for charging station impact analysis and developing AI-based traffic operation algorithms.

We are looking for a dynamic, motivated researcher with a strong technical background. The successful candidate will collaborate with NLR staff and researchers to design and implement data-informed traffic singal control and transportation system planning models to enable efficient and robust transportation system operations and planning.

Responsibilities include:

  • Assist in developing Reinforcement-Learning-based traffic control algorithms.

  • Collaborate with NLR researchers to build high-fidelity traffic simulations.

  • Support development of synthetic population, demand modeling, and total cost of ownership workflows.

  • Process and analyze large-scale transportation datasets.

  • Process and visualize results from simulations scenarios to inform real-time traffic operations and planning decisions.

  • Author, present and assist in the preparation of technical papers, reports and conference proceedings on topics related to data-driven traffic modeling and simulation and their application.

As a year-round intern, this role can adjust the working hours between 20-40 hours depending on your coursework and workload.

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Basic QualificationsMinimum of a 3.0 cumulative grade point average.
Graduate: Must be enrolled as a full-time student in a master's degree program from an accredited institution.
Post Graduate: Earned a master's degree within the past 12 months. Eligible for an internship period of up to one year.
Graduate + PhD: Completed master's degree and enrolled as PhD student from an accredited institution.
Please Note:
Applicants are responsible for uploading official or unofficial school transcripts, as part of the application process.
If selected for position, a letter of recommendation will be required as part of the hiring process.
Must meet educational requirements prior to employment start date.

* Must meet educational requirements prior to employment start date.

Additional Required Qualifications
  • Strong programming skills in Python
  • Experience with data analysis and scientific computing
  • Experience working with large datasets
  • Strong analytical and problem-solving skills
  • Excellent written and verbal communication skills
  • Ability to work independently and collaboratively
Preferred Qualifications
  • Would prefer an intern candidate who is specifically in a PhD program.

  • Experience with transportation modeling or transportation systems analysis

  • Experience with HPC environments (Slurm, clusters, parallel computing)

  • Experience with machine learning and reinforcement learning

  • Experience working with synthetic population and travel demand modeling

  • Experience with SUMO

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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: / Annual Salary Range: $44,500 - $71,200

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 SummaryBenefits include medical, dental, and vision insurance; 403(b) Employee Savings Plan with employer match*; and sick leave (where required by law). 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. Internships projected to be less than 20 hours per week are not eligible for medical, dental, or vision benefits.

* Based on eligibility rules

Badging RequirementNLR 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. Intern assignments extending beyond six months will be subject to this requirement.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.

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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

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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.