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Agent Based Modeling Scientist Jobs in Michigan (NOW HIRING)

Optimal Inc.

Agentic AI Engineer

Warren, MI · On-site

... agent-based solutions into innovative products and research initiatives * Evaluate model ... Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field

Optimal Inc.

Agentic AI Engineer

Warren, MI · On-site

... agent-based solutions into innovative products and research initiatives * Evaluate model ... Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field

Intellectt INC

Plant Modeling Engineer

Warren, MI · On-site

The role involves working with Simulink-based modeling, HiL/SiL environments, electrical schematics ... Bachelor's degree in Mechanical, Electrical, Software, Computer Science, or Aerospace Engineering ...

New

CSAA

This Data Scientist role offers the opportunity to help CSAA Insurance Group anticipate and prepare ... Lead the design, development, and validation of simulation models (discrete-event, agent-based ...

Epitec

Scientist / Research Eng General

Dearborn, MI · On-site

Build and deploy Remaining Useful Life (RUL) models using machine learning and physics-based ... Machine Learning and Data Science * MATLAB and Simulink * Embedded Controls and Diagnostics

Agile Tech Labs

Data Scientist

Detroit, MI · On-site

Job Title: Data Scientist Job Location: Detroit, MI (Hybrid) Job Type: Contract * Develop and ... Experience building AI solutions using LLMs and transformer-based models. * Ability to convert ...

Tech Tammina LLC

Data Scientists Modeling

Dearborn, MI · On-site

Iterate on models and approaches based on performance feedback and evolving business requirements. * Stay up to date with the latest advancements in data science, machine learning, and relevant ...

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Agent Based Modeling Scientist information

What is the difference between Agent Based Modeling Scientist vs Data Scientist?

AspectAgent Based Modeling ScientistData Scientist
Required CredentialsMaster's or PhD in computer science, mathematics, or related fields; experience with modeling and simulationDegree in statistics, computer science, or related fields; proficiency in programming and statistical analysis
Work EnvironmentResearch labs, academia, or industry focused on simulation and modeling projectsBusiness, tech companies, or consulting firms analyzing large datasets
Industry UsageResearch, simulation, complex systems modelingData analysis, predictive modeling, business insights

While both roles require strong analytical skills and programming knowledge, an Agent Based Modeling Scientist specializes in creating simulations of autonomous agents within complex systems, whereas a Data Scientist focuses on analyzing and interpreting large datasets to inform business decisions.

What are the key skills and qualifications needed to thrive as an agent based modeling scientist, and why are they important?

To thrive as an Agent Based Modeling Scientist, you need expertise in computational modeling, systems theory, and a strong background in mathematics or related fields, often supported by an advanced degree. Proficiency with programming languages such as Python, Java, or NetLogo and familiarity with simulation software are typically required. Analytical thinking, problem-solving, and the ability to communicate complex concepts clearly are valuable soft skills in this role. These skills are crucial for accurately developing, interpreting, and conveying insights from agent-based models to inform research or decision-making.

How does an agent based modeling scientist typically collaborate with interdisciplinary teams during a project?

Agent Based Modeling Scientists often work closely with experts from fields such as economics, epidemiology, engineering, and computer science to ensure that models accurately reflect real-world systems. Collaboration usually involves regular meetings to define system parameters, validate model assumptions, and interpret simulation results. Effective communication is essential, as team members may not always be familiar with agent-based modeling concepts. Sharing insights and translating technical findings for broader audiences helps ensure models are both robust and actionable for decision-makers.

What is an agent based modeling scientist?

An Agent Based Modeling (ABM) Scientist is a researcher or professional who develops computational models that simulate the actions and interactions of autonomous agents (such as individuals, groups, or entities) to study complex systems. These scientists use ABM techniques to analyze how the behavior of individual agents leads to collective outcomes, often in fields like biology, economics, social sciences, and epidemiology. Their work involves designing models, running simulations, and interpreting data to gain insights into system dynamics and emergent phenomena.
What are popular job titles related to Agent Based Modeling Scientist jobs in Michigan? For Agent Based Modeling Scientist jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Agent Based Modeling Scientist jobs in Michigan look for? The top searched job categories for Agent Based Modeling Scientist jobs in Michigan are:
What cities in Michigan are hiring for Agent Based Modeling Scientist jobs? Cities in Michigan with the most Agent Based Modeling Scientist job openings:
Agent Based Modeling Scientist jobs near you

LEO Lecturer I for AY26-27

University of Michigan

Ann Arbor, MI • On-site

Full-time

Re-posted 17 days ago

University Of Michigan rating

8.1

Company rating: 8.1 out of 10

Based on 144 frontline employees who took The Breakroom Quiz

155th of 615 rated colleges and universities

Job description

Description
How to Apply
You will be asked to provide the following information: a cover letter discussing your interest in and fit for the position, curriculum vitae, a statement of teaching philosophy and experience, and evidence of teaching excellence (evaluations or awards, if available). Additionally, you will be asked to provide the name and contact information for two letters of support. Please email cscs.recruiting@umich.edu with any questions.
Mode of Work:
Onsite
Job Summary
The Center for the Study of Complex Systems (CSCS) at the University of Michigan is seeking to fill a full-time academic year Lecturer I position. CSCS is a broad, interdisciplinary unit whose faculty use and develop tools from applied mathematics, computation, physics, statistics, engineering, and network theory to understand questions in the social, biological, and physical sciences.
Example classes are listed below. (Precise course load will be discussed/assigned based on the qualifications of the applicant.)
  • CMPLXSYS 100 (Complexity: From Simple Rules to Complex Behavior): In this course, we explore a broad range of introductory topics in complex systems, examining how interactions between individuals can lead to emergent patterns, in systems ranging from cells, to societies, to climate change. The course also provides a friendly introduction to programming in an applied context.
  • CMPLXSYS 251(Computational Social Sciences): Due to the growth in electronic sources such as cell phones, Facebook, Twitter, and other online platforms, researchers now have enormous amounts of data about every aspect of our lives - from what we buy, to where we go, to who we know, to what we believe. This has led to a revolution in social science, as we are able to measure human behavior with precision largely thought impossible just a decade ago. Computational Social Science is an exciting and emerging field that sits at the intersection of computer science, statistics, and social science. This course provides a hands-on, non-technical introduction to the methods and ideas of Computational Social Science. We will discuss how new online data sources and the methods that are being used to analyze them can shed new light on old social science questions, and also ask brand new questions. We will also explore some of the ethical and privacy challenges of living in a world where big data and algorithmic decision-making have become more commonplace. Each week, students will have the opportunity to try their hand at analyzing big data from sources ranging from online dating profiles to New York City taxicabs to #metoo Tweets and other sources. Note that this course is a 4-credit course that includes a weekly, 2-hour lab component in addition to lecture and discussion.
  • CMPLXSYS 270 (Introduction to Agent-Based Modeling): Many systems can be modeled as being composed of agents interacting with one another and their environment. Agent based modeling (ABM) can be used to explain phenomena in the biological and social sciences that are driven by multi-agent interactions, ranging from evolution, to epidemic spread, to flocking, to cooperation, to racial segregation in neighborhoods. Agent based modeling allows us to explore how simple rules governing agent behavior can lead to remarkably complex emergent phenomena. In this course students will use Python to explore and modify well-studied agent based models of complex systems, as well as formulate models of their own.
  • CMPLXSYS 325 (Memes, Measles, and Misinformation): This course explores how contagious processes can help us understand a range of different phenomena observed in the real world- ranging from infectious disease transmission, to the spread of information, misinformation, and disinformation. We also explore the feedbacks and interactions between many of these different transmission systems.
  • CMPLXSYS 391(Introduction to Modeling Political Processes): This class provides an introduction to modeling people and social systems. We learn to construct, manipulate, and evaluate models of people who vote, work, commit crimes, and attend classes. We cover concepts and ideas from game theory, learning theory, complexity theory, and even biology and physics (at a metaphorical level of course.) Though the topics and techniques covered are wide ranging - we analyze among other things the wisdom of crowds, the spread of ideas, the causes of racial segregation, and the emergence of riots, they aggregate into a deep methodological coherence. The kind of understanding you won't get by reading the newspaper. By the end, students will understand the strengths and uses of various modeling approaches used in the social sciences and be able to use them. This is not a mathematics course, but it does require a willingness to think abstractly, to carefully contemplate lots of charts and figures, and to do a little algebra. And above all, a commitment to never reading the newspaper in class.
  • CMPLXSYS 445 (Introduction to Information Theory for the Natural Sciences): This course introduces the basic tools of Information Theory. Entropy, Relative Entropy, and Information, and highlights their utility with applications drawn from various disciplines. After introducing the basics of probability theory and information theory, we explore topics including coding, data compression, channel capacity, thermodynamics, population dynamics, gene transcriptions, network science and more.

This is a single academic year (Fall 2026 and Winter 2027) instructional appointment that may be extended subject to departmental needs and satisfactory performance.
Responsibilities*
The initial appointment period is for the academic year 2026-27. Responsibilities include teaching undergraduate and/or graduate courses as an instructor of record, and/or discussion or lab section leader, depending on the department's needs. Duties are expected to include teaching, developing course materials, evaluating and grading students, and holding regularly scheduled office hours. A typical full-time (100% effort) load is three courses per semester. Full-time and part-time positions are available.
Required Qualifications*
Candidates should have a Master's degree or Ph.D. in Complex Systems or a related field such as physics, applied mathematics, network science, EEB, or sociology, and some college-level teaching experience.
Additional Information
As one of the world's great liberal arts colleges, LSA pushes the boundaries of what is understood about the human experience and the natural world, and we foster the next generation of rigorous and empathetic thinkers, creators, and contributors to the state of Michigan, the nation, and the world. To learn more about LSA's Mission, Vision and Values, please visit lsa.umich.edu/strategicvision.
Mission Statement
The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future.
Union Affiliation
This position is covered under the collective bargaining agreement between the U-M and the Lecturers Employee Organization, AFL-CIO, which contains and settles all matters with respect to wages, benefits, hours and other terms and conditions of employment.
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.
Contact Information
Please contact cscs.recruiting@umich.edu with any questions.
Application Deadline
Review of applications will begin on April 1, 2026, and will continue until the position is filled.
U-M EEO/AA Statement
The University of Michigan is an equal opportunity/affirmative action employer.

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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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