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Mathematical Optimization Postdoc Jobs in Madison, PA

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Mathematical Optimization Postdoc information

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$4

$20

$26

How much do mathematical optimization postdoc jobs pay per hour?

As of Aug 13, 2026, the average hourly pay for mathematical optimization postdoc in Madison, PA is $20.30, according to ZipRecruiter salary data. Most workers in this role earn between $17.69 and $22.50 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.
What cities near Madison, PA are hiring for Mathematical Optimization Postdoc jobs? Cities near Madison, PA with the most Mathematical Optimization Postdoc job openings:
Mathematical Optimization Postdoc jobs near you
Infographic showing various Mathematical Optimization Postdoc job openings in Madison, PA as of July 2026, with employment types broken down into 86% Full Time, 10% Part Time, and 4% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution, with an average salary of $42,222 per year, or $20.3 per hour.

Post-Doctoral Fellow in Operations Research

Carnegie Mellon University

Pittsburgh, PA • On-site

$47K - $64K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Carnegie Mellon University rating

8.6

Company rating: 8.6 out of 10

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Job description

Description
Postdoctoral Position at Carnegie Mellon University
The Heinz College of Information Systems and Public Policy at Carnegie Mellon University is now accepting applications for postdoctoral research fellow positions in operations research and analytics. The positions will investigate the role of data, information, and uncertainty in decision making, with a particular emphasis on robust optimization and the design and operation of resilient, and robust systems for distributed health delivery.
Research at Heinz College (https://www.heinz.cmu.edu/) is driven by a strong passion to understand and improve our society analytically - in areas such as healthcare management, rural health, distributed health delivery, mobility, statistical fairness, privacy, supply chains, organizational behavior, workforce economics, and the future of work. Successful candidates will join an active group of colleagues with expertise spanning operations research, optimization, statistics, information systems, economics, and public policy.
The core research agenda centers on robust optimization theory and its applications to real-world decision-making under uncertainty. Possible topics for the postdoctoral positions include classical robust optimization; distributionally robust optimization and data-driven uncertainty or ambiguity sets; resilient supply chains; rural and distributed health delivery systems; healthcare operations and access; improving mobility; identifying and improving social determinants of health; automation in logistics; AI safety; and understanding the theoretical properties of decision models that naturally arise from these application domains.
The postdoctoral fellows will report primarily to Prof. Peter Zhang and Prof. Holly Wiberg. They will be encouraged to publish in top-tier journals and conferences and may collaborate both within Heinz and across Carnegie Mellon University, including the Tepper School of Business, the Department of Civil and Environmental Engineering, the School of Computer Science, and CMU's broader entrepreneurship ecosystem. Fellows will receive regular mentorship throughout the lifecycle of research projects and will be encouraged to disseminate research findings in major conferences and university seminars. Opportunities may also be available to mentor graduate students and to explore commercialization pathways for research with practical impact.
The appointment is for one year, with an option of renewal for a second year contingent on satisfactory progress. The preferred start date is flexible, with earliest availability in Fall 2026.
Qualifications
Candidates should have a PhD by Fall 2026 in operations research, industrial engineering, management science, computer science, mathematics, statistics, or a closely related field. Successful candidates should have a strong research record in optimization, broadly defined, with solid mathematical foundations in areas such as linear programming, convex optimization, combinatorial optimization, stochastic optimization, or robust optimization. Experience with distributionally robust optimization, machine learning, data-driven methods, healthcare delivery, supply chains, or other applied decision-making problems is especially welcome. Excellent written and oral communication skills are expected.
Application Instructions
Interested candidates should submit the following materials:
• Curriculum vitae, including full publication list;
• Research statement, up to 2 pages, describing past work and future research interests;
• One to two representative publications or preprints;
• Three references.
Applications will be reviewed on a rolling basis and will remain open until the positions are filled

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