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Decision Making Postdoc Jobs in Colorado (NOW HIRING)

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Decision Making Postdoc information

What is a decision making postdoc?

A Decision Making Postdoc is a researcher who has completed their PhD and is conducting advanced research in the field of decision-making. This typically involves studying how individuals or groups make choices, using methods from psychology, neuroscience, economics, or related disciplines. Postdocs in this area often work on experimental design, data analysis, and publishing their findings, while collaborating with faculty and other researchers. The position is usually temporary, intended to further develop scholarly skills and prepare for an academic or industry career.

What are common challenges faced by decision making postdocs in balancing independent research with collaborative projects?

Decision Making Postdocs often need to strike a balance between pursuing their own research interests and contributing to larger lab or team projects. Juggling independent work with collaborative studies can be challenging, especially when timelines or methodologies differ. Success in this role typically involves strong communication skills, flexibility, and effective time management, as well as openness to interdisciplinary feedback. Navigating these dynamics helps postdocs build valuable experience for future academic or industry positions.

What are the key skills and qualifications needed to thrive as a decision making postdoc, and why are they important?

To thrive as a Decision Making Postdoc, you need a PhD in psychology, neuroscience, economics, or a related field, along with a strong background in experimental design and data analysis. Expertise in statistical software (such as R, MATLAB, or Python) and experience with behavioral or neuroimaging methods are typically required. Outstanding analytical thinking, problem-solving abilities, and effective scientific communication skills help you excel in collaborative research environments. These competencies are crucial for producing rigorous research, advancing knowledge in decision-making science, and contributing to interdisciplinary projects.

What is the difference between Decision Making Postdoc vs Data Scientist?

AspectDecision Making PostdocData Scientist
Required CredentialsPhD in relevant field, research experienceBachelor's or Master's in CS, stats, or related field; often a PhD preferred
Work EnvironmentAcademic or research institutions, labsTech companies, finance, healthcare, industry
Employer & Industry UsageResearch-focused roles, academiaIndustry roles, product development, analytics
Common Search & ComparisonDecision Making Postdoc vs Data Scientist

The Decision Making Postdoc primarily focuses on research and theoretical analysis related to decision processes, often within academic or research settings. In contrast, Data Scientists apply data analysis, modeling, and machine learning techniques to solve practical problems in industry. While both roles require strong analytical skills, Decision Making Postdocs emphasize research and theoretical frameworks, whereas Data Scientists focus on data-driven solutions for business applications.

What are popular job titles related to Decision Making Postdoc jobs in Colorado?

For Decision Making Postdoc jobs in Colorado, the most frequently searched job titles are:

What job categories do people searching Decision Making Postdoc jobs in Colorado look for?

The top searched job categories for Decision Making Postdoc jobs in Colorado are:

What cities in Colorado are hiring for Decision Making Postdoc jobs?

Cities in Colorado with the most Decision Making Postdoc job openings:

Decision Making Postdoc jobs near you
Infographic showing various Decision Making Postdoc job openings in Colorado as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 18% Part Time, and 3% Contract. Highlights an 93% Physical, 1% Hybrid, and 6% Remote job distribution.

Postdoctoral Researcher - Mathematical Optimization for Energy Systems

The National Renewable Energy Laboratory (NREL)

Golden, CO • On-site

$76K - $126K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 8 days ago

Job description

Posting Title
Postdoctoral Researcher - Mathematical Optimization for Energy Systems
Location
CO - Golden
Position Type
Postdoc (Fixed Term)
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 Advanced Computing Solutions Group in the NLR Computational Science Center has an opening for a full-time Postdoctoral Researcher - Computational Sciences, with an emphasis on mathematical optimization and its application to the design and control of energy systems. We are looking for a dynamic researcher with a strong technical background to help us transform our energy future through advanced automation, control and decision making.
The successful candidate will have extensive experience with mathematical optimization formulations and algorithms and their application to physical systems. Additionally, the candidate will be familiar with parallel algorithmic approaches for large-scale linear, nonlinear, integer, and stochastic optimization problems. We anticipate that the research will involve integrating Artificial Intelligence (AI) techniques, such as reinforcement learning (RL), with classical mathematical optimization approaches and implementations. We seek candidates capable of pursuing research directions that combine these algorithmic components, using implementations that are suitable for effective utilization of the modern parallel computing architectures that are available at NRL. Candidates with creative problem-solving skills, interest in cross-disciplinary collaboration, and a passion for the mission and goals of both NLR and CMEI are of particular interest.
Responsibilities:
  • Collaborate with domain experts to identify where mathematical optimization constitutes a viable approach and maintain awareness of optimization-related research both at NLR and in the literature more generally.
  • Adopt existing - or develop new - mathematical, computing, and simulation frameworks required to implement and evaluate the performance of optimization algorithms and solutions.
  • Creatively identify new opportunities to leverage AI/RL to augment or enhance classical optimization algorithms and/or formulations.
  • Author publications and contribute to proposals to sustain research directions.

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
  • Experience formulating optimization problems in an algebraic modeling language, e.g., Pyomo, JuMP, PuLP, GAMS.
  • Experience with mathematical optimization solvers, e.g., CPLEX, Gurobi, Xpress, Cbc, Ipopt, and their capabilities.
  • Good understanding of optimization fundamentals, both computational and mathematical.

Preferred Qualifications
  • Familiarity with distributed computing frameworks such as MPI and OpenMP
  • Experience with Pyomo and/or JuMP
  • Experience programming in Python and/or Julia
  • Experience with scalable machine learning frameworks, e.g, PyTorch
  • Experience working with diverse, inclusive, and cross-disciplinary research teams

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.
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.

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