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Graph Theory Jobs (NOW HIRING)

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Discrete Math Tutor

AL · Remote

$18 - $40/hr

Deep knowledge of logic and proof techniques, set theory, combinatorics, graph theory, number theory, recurrence relations, Boolean algebra, algorithms, and formal languages. Ability to explain ...

Varsity Tutors

Discrete Math Tutor

Milwaukee, WI · Remote

$18 - $40/hr

Deep knowledge of logic and proof techniques, set theory, combinatorics, graph theory, number theory, recurrence relations, Boolean algebra, algorithms, and formal languages. Ability to explain ...

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Discrete Math Tutor

Johns Creek, GA · Remote

$18 - $40/hr

Deep knowledge of logic and proof techniques, set theory, combinatorics, graph theory, number theory, recurrence relations, Boolean algebra, algorithms, and formal languages. Ability to explain ...

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Discrete Math Tutor

Atlanta, GA · Remote

$18 - $40/hr

Deep knowledge of logic and proof techniques, set theory, combinatorics, graph theory, number theory, recurrence relations, Boolean algebra, algorithms, and formal languages. Ability to explain ...

Varsity Tutors

Discrete Math Tutor

Memphis, TN · Remote

$18 - $40/hr

Deep knowledge of logic and proof techniques, set theory, combinatorics, graph theory, number theory, recurrence relations, Boolean algebra, algorithms, and formal languages. Ability to explain ...

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Discrete Math Tutor

Provo, UT · Remote

$18 - $40/hr

Deep knowledge of logic and proof techniques, set theory, combinatorics, graph theory, number theory, recurrence relations, Boolean algebra, algorithms, and formal languages. Ability to explain ...

Varsity Tutors

Discrete Math Tutor

Henderson, NV · Remote

$18 - $40/hr

Deep knowledge of logic and proof techniques, set theory, combinatorics, graph theory, number theory, recurrence relations, Boolean algebra, algorithms, and formal languages. Ability to explain ...

Varsity Tutors

Discrete Math Tutor

Cleveland, OH · Remote

$18 - $40/hr

Deep knowledge of logic and proof techniques, set theory, combinatorics, graph theory, number theory, recurrence relations, Boolean algebra, algorithms, and formal languages. Ability to explain ...

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How much do graph theory jobs pay per hour?

As of Aug 16, 2026, the average hourly pay for graph theory in the United States is $16.83, according to ZipRecruiter salary data. Most workers in this role earn between $16.11 and $17.55 per hour, depending on experience, location, and employer.

Is graph theory worth studying?

Graph theory is a fundamental area in computer science, mathematics, and network analysis, with applications in data structures, algorithms, and optimization. Studying graph theory can enhance problem-solving skills and open opportunities in fields like software development, data analysis, and research. Proficiency in graph algorithms and tools such as network modeling is valuable for many technical roles.

What are the key skills and qualifications needed to thrive in the graph theory position, and why are they important?

To excel in a Graph Theory role, candidates typically need strong mathematical analysis skills, a background in discrete mathematics or computer science, and often an advanced degree such as a Master's or Ph.D. in a related field. Familiarity with programming languages such as Python or C++, alongside expertise in relevant computational libraries and algorithm development tools, is highly valued. Strong problem-solving abilities, attention to detail, and collaborative communication enhance performance in team-based research or applied project settings. These combined skills are critical for developing innovative solutions to complex problems and advancing the practical applications of graph theory across fields like network analysis, data science, and logistics.

What is a graph theory job?

A Graph Theory job involves applying mathematical concepts of graphs—nodes (vertices) connected by edges—to solve complex problems in computer science, data analysis, networking, and optimization. Professionals in this field work in areas such as cybersecurity, machine learning, bioinformatics, and logistics, designing algorithms and models for efficient processing of interconnected data. Roles may include research scientists, data scientists, software engineers, or operations researchers. Strong skills in discrete mathematics, algorithm design, and programming (e.g., Python, C++, or R) are typically required.

What are some of the primary industries that employ professionals specializing in graph theory?

Professionals with expertise in Graph Theory are highly sought after in industries such as technology (especially in software development and artificial intelligence), telecommunications, logistics and transportation, and finance. They often work on optimizing networks, analyzing large data sets, designing algorithms, or modeling complex systems. These roles can be found at research institutions, universities, tech companies, and consulting firms. Depending on the industry, you may collaborate with data scientists, engineers, and other specialists to solve unique and impactful challenges.

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Graph Theory jobs near you
Infographic showing various Graph Theory job openings in the United States as of August 2026, with employment types broken down into 33% Full Time, and 67% Contract. Highlights an 100% In-person job distribution, with an average salary of $35,000 per year, or $16.8 per hour.

RESEARCH FELLOW - NSF - Granular Materials Using Graph Theory

University of Michigan

Ann Arbor, MI • On-site

Full-time

Posted 9 days ago

University Of Michigan rating

8.1

Company rating: 8.1 out of 10

Based on 145 frontline employees who took The Breakroom Quiz

162nd of 618 rated colleges and universities

Job description

How to Apply
Applications should be sent to [email protected] and [email protected] with the subject line: Postdoctoral Application - Granular materials using graph theory.
Interested applicants should submit:
  1. Cover letter describing research interests and relevant experience (or information embedded in email).
  2. Curriculum vitae.
  3. Contact information for three references.

Who We Are
At Michigan Engineering, we develop the talent and technologies that move society forward and serve our state and national interests. Through discovery and innovation, we create the foundational knowledge and practical technologies to solve not only today's most pressing challenges, but also power industries and change lives. Our programs and community are designed to promote personal well-being and achievement - enabling everyone to unlock their potential and contribute with confidence.
Job Summary
The Department of Mechanical Engineering at the University of Michigan invites applications for a Postdoctoral Research Fellow position as part of an NSF-funded project focused on understanding the relationships among particle geometry, packing structure, force transmission, and mechanical properties in dense assemblies of faceted, nonspherical granular particles. This multi-PI project integrates graph/network theory, granular mechanics, 3D X-ray diffraction and imaging, and discrete element method simulations. The successful candidate will join a collaborative experimental-computational team led by Prof. Hongyi Xiao and Prof. Ashley Bucsek at the University of Michigan and with opportunities at national synchrotron facilities.
One of the hallmarks of granular materials is the complexity of their particle shapes. Real-world granular materials often consist of particles with flat surfaces, edges, and corners, including minerals formed through crystallization, ceramics produced by comminution, and building blocks used in durable ancient architecture. This project will use graph theory to represent and analyze the contact networks of faceted, nonspherical particles. Graph-based descriptors will be constructed from X-ray-based 3D in-situ characterization methods, including High-Energy Diffraction Microscopy and Micro-Computed Tomography, and supported by Discrete Element Method simulations.
The postdoctoral fellow will contribute to one or more aspects of the project, including graph/network construction and analysis, 3D in-situ X-ray diffraction and imaging experiments, and discrete element method simulations. Applicants with strong expertise in any one of these areas and an interest in interdisciplinary collaboration are encouraged to apply.
Responsibilities*
The successful candidate will:
  • Work closely with an integrated experimental, computational, and data-analysis team at the University of Michigan.
  • Develop and apply graph/network-based representations of faceted granular assemblies.
  • Contribute to experimental design, data analysis, and/or computational modeling, depending on expertise.
  • Prepare manuscripts for peer-reviewed publication and present results at national and international conferences.
  • Contribute to project reporting and participate in regular team meetings.
  • Engage in a highly collaborative, multidisciplinary research environment spanning solid mechanics, materials science, X-ray characterization, condensed matter physics, granular mechanics, and network theory.

Required Qualifications*
Applicants should have:
  • A Ph.D. in physics, mechanical engineering, materials science and engineering, chemical engineering, computational science, or a closely related field.
  • A strong background in one or more of the following areas: graph/network analysis, solid mechanics, materials science, soft condensed matter physics, or computational modeling.
  • Experience with data analysis or computational tools using MATLAB, Python, or similar platforms.
  • Demonstrated ability to conduct independent research and publish in peer-reviewed journals.
  • Strong communication skills and interest in collaborative, team-based research.

Desired Qualifications*
Preferred candidates will have experience in one or more of the following areas:
  • Graph-based network analysis for complex particle systems.
  • 3D X-ray diffraction, high-energy diffraction microscopy, micro-computed tomography, and the associated analysis methods.
  • Discrete element method and/or finite element method simulations.
  • Physics of granular materials related to jamming, packing and deformation.

Modes of Work
Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes .
Additional Information
Position Details:
  • Location: Ann Arbor, Michigan, U.S.
  • Department: Mechanical Engineering, University of Michigan
  • Start date: Preferred start date September - December 2026
  • Appointment length: Initial one-year appointment, renewable based on performance for an additional one to two years.
  • Funding: U.S. National Science Foundation
  • Supervisors: Prof. Hongyi Xiao (Department of Mechanical Engineering) and Prof. Ashley Bucsek (Department of Mechanical Engineering, Department of Materials Science and Engineering)

Background Screening
The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third-party administrator to conduct background checks. Background checks are performed in compliance with the Fair Credit Reporting Act.
Application Deadline
Job openings are posted for a minimum of seven calendar days. The review and selection process may begin as early as the eighth day after posting. This opening may be removed from posting boards and filled at any time after the minimum posting period has ended.
U-M EEO Statement
The University of Michigan is an Equal Opportunity Employer. We are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants, including protected veterans and individuals with disabilities.
Job Detail
Job Opening ID
281393
Working Title
RESEARCH FELLOW - NSF - Granular Materials Using Graph Theory
Job Title
RESEARCH FELLOW
Work Location
Ann Arbor Campus
Ann Arbor, MI
Modes of Work
Onsite
Full/Part Time
Full-Time
Regular/Temporary
Regular
FLSA Status
Exempt
Organizational Group
College Engineering
Department
CoE Mechanical Engineering
Posting Begin/End Date
8/07/2026 - 8/21/2026
Career Interest
Research Fellows

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About University of Michigan

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The University of Michigan (U-M), based in Ann Arbor, MI, US, is one of America's most esteemed institutions in higher education. Established in 1817, it presides in the industry of education and research, providing a range of services including undergraduate, graduate, and professional education programs. Complementing this is an extensive research activity that has significantly contributed to various fields, from healthcare to engineering, humanities to sports. Upholding its mission "to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values", U-M consistently ranks among the top universities globally, a testament to its tradition of excellence in learning and research, and a deep commitment to innovation and discovery.

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