Postdoctoral Researcher in uncertainty quantification and prediction reliability

Posting Title

Postdoctoral Researcher in uncertainty quantification and prediction reliability

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Location

CO - Golden

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Position Type

Postdoc (Fixed Term)

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Hours Per Week

40

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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 Artificial Learning and Intelligent Systems group in NLR’s Computational Science Center has an immediate opening for a Postdoctoral Researcher to pursue a cross-disciplinary research project in uncertainty quantification, with particular emphasis on evaluating prediction reliability across scales (lab-scale to pilot-scale) in applications relevant to the DOE Office of Critical Minerals and Energy Innovation. We are looking for an individual who can reason about uncertainty arising from sparse data, extrapolation, and potentially incorrect model structure.

The successful applicant will develop methods to quantify uncertainty in cross-scale prediction models and identify when a model is operating beyond the conditions where its predictions are reliable. The deeper problem is that a model trained at one scale may be systematically wrong at another because the underlying relationships have changed, important mechanisms are missing, or the available evidence does not adequately constrain the prediction. The successful applicant will conduct original methods research to address this challenge. We are looking for individuals with background in applied statistics, uncertainty quantification for scientific computing, statistical learning theory, reliable or trustworthy machine learning, out-of-distribution detection and distributionally robust methods, and/or model validation and discrepancy modeling.

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Basic Qualifications

Must be a recent PhD graduate within the last three years.

* Must meet educational requirements prior to employment start date.

Additional Required Qualifications

• Demonstrated experience with statistical modeling including strong grounding in statistical inference, Bayesian methods, probabilistic modeling, and uncertainty propagation.
• Demonstrated experience with uncertainty quantification including experience distinguishing and estimating aleatoric and epistemic uncertainty, and model-form or structural uncertainty.
• Demonstrated understanding of methods for assessing whether predicted uncertainty corresponds to actual prediction errors, especially with limited validation data.
• Demonstrated understanding of distribution shift and out-of-distribution detection for identifying when new conditions or data differ meaningfully from the training domain.
• Demonstrated experience with model discrepancy and structural uncertainty to enable understanding how missing physics, incorrect assumptions, or changing mechanisms affect model reliability.
• Demonstrated experience evaluating predictions outside the training domain, including methods that can recognize when extrapolation is unsafe or unsupported.
• Excellent communication skills
• Demonstrated experience working in multi-disciplinary teams and collaborative software development
• Demonstrated programming experience (python, Julia, R) and version control software

Preferred Qualifications

· Self-motivated, creative, and independent thinker

· Open-minded and eager to learn about new application challenges

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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: Postdoctoral Researcher / 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-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; and paid holidays. 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.

* 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.

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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.

About Us

The National Laboratory of the Rockies (NLR) is the U.S. Department of Energy's primary national laboratory for critical minerals, energy innovation, and energy security. With locations in Golden and Boulder, Colorado, Fairbanks, Alaska, and a satellite office in Washington, D.C., NLR bridges foundational research with practical applications to develop and bring to scale new energy materials and technologies that lower energy costs, drive economic growth, and deliver abundant and reliable energy.

NLR is subject to Department of Energy (DOE) access restrictions. All candidates must be authorized to access the facility per DOE rules and guidance within a reasonable time frame for the specified position in order to be considered for an interview and for hiring. DOE rules for site access during the interview process depend on whether the candidate is interviewed on-site, off-site, or via telephone or videoconference. 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. Additionally, DOE contractor employees are prohibited from participating in certain Foreign Government Talent Recruitment Programs (FGTRPs). If a candidate is currently participating in an FGTRP, they will be required to disclose their participation after receiving an offer of employment and may be required to disengage from participation in the FGTRP prior to commencing employment. Any offer of employment is conditional on the ability to obtain work authorization and to be granted access to NLR by the Department of Energy (DOE).

Drug Free Workplace

NLR is committed to maintaining a drug-free workplace in accordance with 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.