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Environmental Science Graduate Jobs in Colorado (NOW HIRING)

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Environmental Science Graduate information

See Colorado salary details

$43.1K

$88.5K

$129.3K

How much do environmental science graduate jobs pay per year?

As of Sep 3, 2026, the average yearly pay for environmental science graduate in Colorado is $88,457.00, according to ZipRecruiter salary data. Most workers in this role earn between $78,900.00 and $103,600.00 per year, depending on experience, location, and employer.

What jobs can you get with an environmental science degree?

Graduates with an environmental science degree can pursue a variety of careers, including roles such as environmental consultant, conservation scientist, environmental educator, sustainability specialist, and environmental analyst. They may work for government agencies, non-profit organizations, private companies, or research institutions. The degree provides a strong foundation in ecological principles, data analysis, and problem-solving, making graduates valuable in addressing environmental challenges and developing sustainable solutions.

What types of projects do environmental science graduates typically work on early in their careers?

As an Environmental Science Graduate, you can expect to contribute to a variety of projects such as environmental impact assessments, data collection and analysis for pollution monitoring, and fieldwork related to habitat restoration. Early-career roles often involve collaborating with multidisciplinary teams, including engineers, ecologists, and policy experts, to address real-world environmental challenges. These projects provide hands-on experience and the opportunity to develop specialized skills that can lead to advancement into research, consulting, or project management roles.

What are the key skills and qualifications needed to thrive as an environmental science graduate, and why are they important?

To thrive as an Environmental Science Graduate, you need a solid grounding in environmental principles, data analysis, and scientific research, often supported by a relevant bachelor's degree. Familiarity with GIS software, statistical tools like R or Python, and laboratory techniques is typically required. Strong communication, problem-solving, and teamwork skills help you effectively collaborate and convey scientific findings to diverse audiences. These skills are crucial for addressing complex environmental challenges and contributing meaningfully to sustainability initiatives.

What is the difference between Environmental Science Graduate vs Environmental Technician?

AspectEnvironmental Science GraduateEnvironmental Technician
Required CredentialsBachelor's degree in environmental science or related fieldAssociate degree or relevant certification, sometimes a bachelor's
Work EnvironmentResearch labs, fieldwork, data analysisField sites, laboratories, environmental monitoring
Employer & Industry UsageUniversities, research institutions, government agenciesEnvironmental consulting firms, government agencies, industrial sites
Common Search & ComparisonEntry-level roles, career development, educational backgroundTechnical roles, fieldwork, practical skills

Environmental Science Graduates typically hold a bachelor's degree and focus on research, data analysis, and environmental policy. Environmental Technicians often have an associate degree or certification and perform field sampling, monitoring, and technical tasks. Both roles are essential in environmental work, but they differ in education level, job responsibilities, and work settings.

Is graduate school worth it for environmental science?

For environmental science graduates, attending graduate school can enhance specialized knowledge, research skills, and qualifications for advanced roles or academia. However, many entry-level positions in environmental science are available with a bachelor's degree, and practical experience or certifications like GIS or environmental impact assessments can also be valuable. The decision depends on career goals and the specific requirements of desired positions.

Is it worth getting a master's in environmental science?

For environmental science graduates, obtaining a master's degree can enhance job prospects, increase earning potential, and qualify for specialized roles such as environmental consultants or policy analysts. It often provides advanced skills in data analysis, environmental modeling, and regulatory understanding, which are valued in the field.

What can I do with a master's degree in environmental science?

An environmental science graduate with a master's degree can pursue roles such as environmental analyst, conservation scientist, environmental consultant, or sustainability coordinator. These positions often require skills in data analysis, environmental regulations, and fieldwork, and may involve working for government agencies, consulting firms, or non-profit organizations.

What are popular job titles related to Environmental Science Graduate jobs in Colorado?

For Environmental Science Graduate jobs in Colorado, the most frequently searched job titles are:

What cities in Colorado are hiring for Environmental Science Graduate jobs?

Cities in Colorado with the most Environmental Science Graduate job openings:

Infographic showing various Environmental Science Graduate job openings in Colorado as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 19% Part Time, 1% Temporary, and 2% Contract. Highlights an 73% Physical, 4% Hybrid, and 23% Remote job distribution, with an average salary of $88,457 per year, or $42.5 per hour.

Graduate Intern - LLM Reliability and Uncertainty for AI Science Assistants

Nrel

Golden, CO

Full-time

Medical, Dental, Vision, Retirement

Re-posted 14 days ago


Job description

Posting TitleGraduate Intern - LLM Reliability and Uncertainty for AI Science Assistants

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LocationCO - Golden

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Position TypeIntern (Fixed Term)

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Hours Per Week40

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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 AI, Learning and Intelligent Systems group in the NLR Computational Science Center has an opening for a graduate student researcher in LLM Reliability and Uncertainty for AI Science Assistants. The researcher will investigate methods for quantifying uncertainty in LLM-based science assistants over multi-turn scientific dialogue, with an emphasis on flagging when a scientific question or task is underspecified or ill-posed. In practice, scientific questions can be vague, open-ended, or underdetermined. LLM-based assistants can quietly insert their own assumptions into such requests to fill the gap instead of raising concerns to their human counterpart. This internship will investigate if the assistant's internal representations can be probed to detect these instances so they may be flagged for the user or used to trigger clarifying questions. We are looking for a dynamic, motivated researcher with a strong technical background and an interest in AI for science, uncertainty-aware machine learning, human-AI scientific workflows, and trustworthy AI. The successful candidate must be able to work at the intersection of machine learning research and practical AI system integration.

Responsibilities include:

  • Research and evaluate uncertainty quantification and hallucination detection methods for multi-turn, agentic scientific workflows
  • Develop probing methods that predict, from a model's internal representations, when a scientific task specification is incomplete or inconsistent and a clarifying question is warranted
  • Build and instrument evaluation pipelines that capture and analyze model internal states over multi-turn scientific dialogue on HPC systems
  • Conduct experiments and analyze model behavior across computational science domains and established benchmarks
  • Contribute to technical documentation, research reports, publications, and presentations summarizing project progress and findings
  • Develop, test, and maintain high-quality research code and evaluation pipelines

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Basic QualificationsMinimum of a 3.0 cumulative grade point average.
Undergraduate: Must be enrolled as a full-time student in a bachelor's degree program from an accredited institution.
Post Undergraduate: Earned a bachelor's degree within the past 12 months. Eligible for an internship period of up to one year.
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
  • Familiarity with large language models, including agentic, tool-using, or multi-turn conversational LLM systems
  • Experience developing or evaluating machine learning models for classification, uncertainty estimation, or related tasks
  • Knowledge of probabilistic machine learning or uncertainty quantification concepts
  • Hands-on experience with open-weight LLMs and modern deep learning frameworks
  • Experience running Python code on HPC or multi-GPU systems
  • Strong software engineering and debugging skills
  • Ability to work independently while collaborating effectively in a multidisciplinary research environment
Preferred Qualifications
  • Research experience related to hallucination detection, uncertainty quantification, interpretability, explainability, or trustworthy AI
  • Familiarity with representation probing or mechanistic interpretability methods
  • Experience with LLM benchmarking and evaluation, including multi-turn or conversational agent evaluation and LLM-as-a-judge protocols
  • Experience with scientific question-answering systems, AI for science applications, or scientific agent frameworks
  • Coursework or research background in a computational science domain (e.g., fluid mechanics, solid mechanics, materials science, or numerical methods for PDEs)

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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.