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Mathematical Optimization Postdoc Jobs (NOW HIRING)

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Mathematical Optimization Postdoc information

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How much do mathematical optimization postdoc jobs pay per hour?

As of Jul 7, 2026, the average hourly pay for mathematical optimization postdoc in the United States is $22.32, according to ZipRecruiter salary data. Most workers in this role earn between $19.47 and $24.76 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Mathematical Optimization Postdoc, and why are they important?

To thrive as a Mathematical Optimization Postdoc, you need an advanced degree (typically a PhD) in mathematics, operations research, or a related field, with a deep understanding of optimization theory and algorithms. Familiarity with programming languages such as Python, MATLAB, or C++, and experience with optimization software like Gurobi or CPLEX, are commonly required. Strong analytical thinking, problem-solving abilities, and effective collaboration and communication skills set outstanding candidates apart. These skills are crucial for conducting innovative research, publishing results, and contributing to interdisciplinary projects in academic or industry settings.

What is the difference between Mathematical Optimization Postdoc vs Operations Research Analyst?

AspectMathematical Optimization PostdocOperations Research Analyst
Required credentialsPhD in mathematics, operations research, or related fieldBachelor's or master's degree in operations research, mathematics, or engineering
Work environmentAcademic research, university labs, research institutesCorporate, government agencies, consulting firms
Employer and industry usageUniversities, research institutionsBusinesses, government, consulting
Common search intentResearch, academic positions, postdoctoral opportunitiesApplying optimization techniques in industry, problem-solving roles

The Mathematical Optimization Postdoc primarily focuses on academic research and advancing theoretical methods in optimization, often within universities or research institutions. In contrast, Operations Research Analysts apply these techniques in practical industry settings to solve real-world problems. While both roles require strong analytical skills, the postdoc emphasizes research and publication, whereas the analyst role centers on implementation and operational decision-making.

What are some common challenges faced by Mathematical Optimization Postdocs when transitioning from academic research to industry projects?

Mathematical Optimization Postdocs often find the transition to industry projects challenging due to differences in project timelines, the need for practical and scalable solutions, and collaboration with interdisciplinary teams. In industry, optimization problems may be less theoretically defined and require rapid prototyping, frequent communication with stakeholders, and adaptability to changing business needs. Developing strong communication skills and learning to balance rigorous research with practical constraints are key to succeeding in this environment.

What is a Mathematical Optimization Postdoc?

A Mathematical Optimization Postdoc is a researcher who has completed their PhD and is engaged in advanced research focused on mathematical optimization. This field involves developing and analyzing algorithms and mathematical models to find the best solutions to complex problems, often under constraints. Postdocs in this area typically work at universities, research institutes, or in industry, collaborating with other scientists and publishing their findings. Their work may be applied to areas such as logistics, machine learning, finance, or engineering. The position is usually temporary, lasting from one to three years, and serves as a stepping stone to permanent academic or industry roles.
More about Mathematical Optimization Postdoc jobs
What cities are hiring for Mathematical Optimization Postdoc jobs? Cities with the most Mathematical Optimization Postdoc job openings:
What states have the most Mathematical Optimization Postdoc jobs? States with the most job openings for Mathematical Optimization Postdoc jobs include:
Infographic showing various Mathematical Optimization Postdoc job openings in the United States as of July 2026, with employment types broken down into 66% Full Time, 33% Part Time, and 1% Nights. Highlights an 94% Physical, and 6% Remote job distribution, with an average salary of $46,417 per year, or $22.3 per hour.
Postdoctoral Researcher - Mathematical Optimization for Energy Systems

Postdoctoral Researcher - Mathematical Optimization for Energy Systems

The National Renewable Energy Laboratory (NREL)

Golden, CO โ€ข On-site

$76K - $126K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 23 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
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