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How much do mathematical optimization postdoc jobs pay per hour?

As of Sep 9, 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 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.

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 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.

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Mathematical Optimization Postdoc jobs near you
Infographic showing various Mathematical Optimization Postdoc job openings in the United States as of September 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $46,417 per year, or $22.3 per hour.

Electrochemical Engineering Postdoctoral Scholar

Berkeley, CA • On-site

Lawrence Berkeley National Laboratory
5 - 10K employees
Learn more about Lawrence Berkeley National Laboratoryexternal

Full-time

Re-posted 5 days ago

Lawrence Berkeley National Laboratory rating

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Company rating: 9.5 out of 10

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2nd of 121 rated laboratories

Job description

In this exciting role, you will simulate mathematically fuel cell systems and other related electrochemical devices and their components under both steady state and transient operation in The Energy Conversion Group at Energy Technologies and Systems Division of the Energy Technologies Area. Your work will entail model development, validation, and execution including collaboration with research partners, to verify and explain predicted trends seen in experimental data. The model should identify critical barriers and provide strategies to enable performance optimization and durability mitigation. In addition to cell level modeling, particular emphasis will be on understanding multi-ion transport and durability stressors including structure/function relationships across multiple time and length scales. Additionally, incorporating AI/ML into the multiphysics models via surrogate models or other data-driven methods will be a focus in this position.
We're here for the same mission, to bring science solutions to the world. Join our team and YOU will play a supporting role in our goal to address global challenges! Have a high level of impact and work for an organization associated with 17 Nobel Prizes!
You will:
  • Develop and refine mathematical models to examine multidimensional, multiphysics, transport within an electrochemical cell including its various constitutive layers (e.g., porous transport layers, gas-diffusion and microporous layers, membrane, and catalyst layers).
  • Analyze the results to examine limiting factors in performance as well as identify areas of deficiency in the model and propose new mathematical constructs to deal with them.
  • Pursue microstructural simulations of transient phenomena within single components.
  • Use AI/ML approaches (e.g., physics-informed neural networks) for surrogate model development
  • Validate model activities and comparison of simulation to experimental data for both input parameters and output results.
  • Publish original research in peer-reviewed journals; contribute to scientific publications; present research through talks and posters at conferences, workshops, and multi-investigator meetings.
  • Adhere with the Berkeley Lab and ETA safety requirements.
  • Work on meeting milestones and reporting them to DOE and industrial sponsors
  • Collaborate and work with a team of researchers from diverse backgrounds, and interface with research teams from across industry, academia, and national laboratories

Additional Responsibilities as needed:
  • Work on experimental characterization of cell performance and measurement of component properties.
  • Interact with the LBNL fuel cell and electrochemistry community (with extensive experience in batteries, modeling of batteries and fuel cells, electrode material synthesis, spectroscopy, detailed diagnostics, and cell design) to aid in electrochemistry research.
  • Participate in professional society activities.

We are looking for:
  • PhD in chemical engineering, mechanical engineering, applied physics, or closely related field.
  • Experience with mathematical modeling (i.e., continuum modeling) including in the application of transport phenomena in fuel cells or related devices and at various scales.
  • Familiarity with high performance computing and code development and use including the use of AI/ML and surrogate model development for multiscale analysis
  • Excellent communication skills, both oral and written as well as technical writing.
  • Ability to learn rapidly and integrate new fields to demonstrate creative problem-solving skills
  • Ability and willingness to work in a team environment and collaborate with researchers from various backgrounds
  • Ability to work as an independent researcher with a high level of scientific judgment and initiative.
  • Knowledge of electrochemistry and related diagnostic methods and materials for fuel cells (both low and intermediate temperatures).
  • Knowledge of constitutive relations and continuum theories.

Desired skills/knowledge:
  • Demonstrated ability to take initiative for tackling cross-disciplinary research problems from initiation to meaningful conclusion.
  • Experience with electrochemistry, hydrogen fuel cells, and transport phenomena.
  • Demonstrated strong experience with finite-element methods and Comsol.
  • Familiarity with machine learning and associated big data techniques.

For consideration, please apply with the following application materials:
  • Cover Letter - Describe your interest in this position and the relevance of your background.
  • Curriculum Vitae (CV) or Resume.

Additional information:
  • Appointment type: This is a full-time 2 years, postdoctoral appointment with the possibility of renewal based upon satisfactory job performance, continuing availability of funds and ongoing operational needs. You must have less than 3 years of paid postdoctoral experience. Salary for Postdoctoral positions depends on years of experience post-degree.
  • Salary range: The monthly salary range for this position is $6,891 / mo - $7,609.00 / mo and is expected to start at $6,891 / mo or above. Postdoctoral positions are paid on a step schedule per union contract and salaries will be predetermined based on postdoctoral step rates. Each step represents one full year of completed post-Ph.D. postdoctoral and/or related research experience.
  • Background check: This position is subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment.
  • Work modality: This position will be primarily performed on-site at Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA.
  • Union Represented: This position is represented by a union for collective bargaining purposes.

Want to learn more about working at Berkeley Lab? Please visit: careers.lbl.gov
Equal Employment Opportunity Employer: The foundation of Berkeley Lab is our Stewardship Values: Team Science, Service, Trust, Innovation, and Respect; and we strive to build community with these shared values and commitments. Berkeley Lab is an Equal Opportunity Employer. We heartily welcome applications from all who could contribute to the Lab's mission of leading scientific discovery, excellence, and professionalism. In support of our rich global community, all qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories under State and Federal law.
Misconduct Disclosure Requirement: As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct, are currently being investigated for misconduct, left a position during an investigation for alleged misconduct, or have filed an appeal with a previous employer.

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