Associate Research Scientist
New York, NY · On-site
... differential equations, and agent-based modeling approaches. The candidate will integrate ... Experience mentoring trainees and collaborating within multidisciplinary research teams.
Associate Research Scientist
New York, NY · On-site
... differential equations, and agent-based modeling approaches. The candidate will integrate ... Experience mentoring trainees and collaborating within multidisciplinary research teams.
MS&A focus areas include agent-based modeling, red vs blue simulations, militaryutilityand capability drawdown,killchaineffectiveness, enterprise architecture resiliency, and command and control (C2 ...
MS&A focus areas include agent-based modeling, red vs blue simulations, militaryutilityand capability drawdown,killchaineffectiveness, enterprise architecture resiliency, and command and control (C2 ...
MS&A focus areas include agent-based modeling, red vs blue simulations, militaryutilityand capability drawdown,killchaineffectiveness, enterprise architecture resiliency, and command and control (C2 ...
MS&A focus areas include agent-based modeling, red vs blue simulations, militaryutilityand capability drawdown,killchaineffectiveness, enterprise architecture resiliency, and command and control (C2 ...
MS&A focus areas include agent-based modeling, red vs blue simulations, militaryutilityand capability drawdown,killchaineffectiveness, enterprise architecture resiliency, and command and control (C2 ...
MS&A focus areas include agent-based modeling, red vs blue simulations, militaryutilityand capability drawdown,killchaineffectiveness, enterprise architecture resiliency, and command and control (C2 ...
MS&A focus areas include agent-based modeling, red vs blue simulations, militaryutilityand capability drawdown,killchaineffectiveness, enterprise architecture resiliency, and command and control (C2 ...
MS&A focus areas include agent-based modeling, red vs blue simulations, militaryutilityand capability drawdown,killchaineffectiveness, enterprise architecture resiliency, and command and control (C2 ...
MS&A focus areas include agent-based modeling, red vs blue simulations, military utility and capability drawdown, killchain effectiveness, enterprise architecture resiliency, and command and control ...
MS&A focus areas include agent-based modeling, red vs blue simulations, military utility and capability drawdown, killchain effectiveness, enterprise architecture resiliency, and command and control ...
Epidemiologist I
Detroit, MI · On-site
... agent-based modeling techniques, Epidemiological analysis methods, Statistical sampling methods, and Healthcare-associated infection surveillance methods to complete necessary tasks; conduct library ...
Epidemiologist I
Detroit, MI · On-site
... agent-based modeling techniques, Epidemiological analysis methods, Statistical sampling methods, and Healthcare-associated infection surveillance methods to complete necessary tasks; conduct library ...
MS&A focus areas include agent-based modeling, red vs blue simulations, military utility and capability drawdown, killchain effectiveness, enterprise architecture resiliency, and command and control ...
MS&A focus areas include agent-based modeling, red vs blue simulations, military utility and capability drawdown, killchain effectiveness, enterprise architecture resiliency, and command and control ...
... agent-based modeling techniques, Epidemiological analysis methods, Statistical sampling methods, and Healthcare-associated infection surveillance methods to complete necessary tasks; conduct library ...
... agent-based modeling techniques, Epidemiological analysis methods, Statistical sampling methods, and Healthcare-associated infection surveillance methods to complete necessary tasks; conduct library ...
LEO Lecturer I for AY26-27
Ann Arbor, MI · On-site
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 ...
LEO Lecturer I for AY26-27
Ann Arbor, MI · On-site
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 ...
MS&A focus areas include agent-based modeling, red vs blue simulations, military utility and capability drawdown, killchain effectiveness, enterprise architecture resiliency, and command and control ...
MS&A focus areas include agent-based modeling, red vs blue simulations, military utility and capability drawdown, killchain effectiveness, enterprise architecture resiliency, and command and control ...
Understanding of agent-based modeling, multi-agent systems, or reinforcement learning. * Experience building applications with LLMs or generative AI models. * Familiarity with API development ...
Understanding of agent-based modeling, multi-agent systems, or reinforcement learning. * Experience building applications with LLMs or generative AI models. * Familiarity with API development ...
Understanding of agent-based modeling, multi-agent systems, or reinforcement learning. * Experience building applications with LLMs or generative AI models. * Familiarity with API development ...
Understanding of agent-based modeling, multi-agent systems, or reinforcement learning. * Experience building applications with LLMs or generative AI models. * Familiarity with API development ...
Understanding of agent-based modeling, multi-agent systems, or reinforcement learning. * Experience building applications with LLMs or generative AI models. * Familiarity with API development ...
Understanding of agent-based modeling, multi-agent systems, or reinforcement learning. * Experience building applications with LLMs or generative AI models. * Familiarity with API development ...
Understanding of agent-based modeling, multi-agent systems, or reinforcement learning. * Experience building applications with LLMs or generative AI models. * Familiarity with API development ...
Understanding of agent-based modeling, multi-agent systems, or reinforcement learning. * Experience building applications with LLMs or generative AI models. * Familiarity with API development ...
Understanding of agent-based modeling, multi-agent systems, or reinforcement learning. * Experience building applications with LLMs or generative AI models. * Familiarity with API development ...
Understanding of agent-based modeling, multi-agent systems, or reinforcement learning. * Experience building applications with LLMs or generative AI models. * Familiarity with API development ...
Understanding of agent-based modeling, multi-agent systems, or reinforcement learning. * Experience building applications with LLMs or generative AI models. * Familiarity with API development ...
Understanding of agent-based modeling, multi-agent systems, or reinforcement learning. * Experience building applications with LLMs or generative AI models. * Familiarity with API development ...
Understanding of agent-based modeling, multi-agent systems, or reinforcement learning. * Experience building applications with LLMs or generative AI models. * Familiarity with API development ...
Understanding of agent-based modeling, multi-agent systems, or reinforcement learning. * Experience building applications with LLMs or generative AI models. * Familiarity with API development ...
Understanding of agent-based modeling, multi-agent systems, or reinforcement learning. * Experience building applications with LLMs or generative AI models. * Familiarity with API development ...
Understanding of agent-based modeling, multi-agent systems, or reinforcement learning. * Experience building applications with LLMs or generative AI models. * Familiarity with API development ...
Understanding of agent-based modeling, multi-agent systems, or reinforcement learning. * Experience building applications with LLMs or generative AI models. * Familiarity with API development ...
Understanding of agent-based modeling, multi-agent systems, or reinforcement learning. * Experience building applications with LLMs or generative AI models. * Familiarity with API development ...
Trainee Agent Based Modeling information
See salary details
$11.78 - $13.79
2% of jobs
$13.79 - $15.80
9% of jobs
$16.96 is the 25th percentile. Wages below this are outliers.
$15.80 - $17.81
23% of jobs
The median wage is $18.85 / hr.
$17.81 - $19.82
29% of jobs
$21.29 is the 75th percentile. Wages above this are outliers.
$19.82 - $21.83
15% of jobs
$21.83 - $23.84
6% of jobs
$23.84 - $25.85
2% of jobs
$25.85 - $27.86
2% of jobs
$27.86 - $29.87
4% of jobs
$29.87 - $31.88
4% of jobs
$31.88 - $33.89
2% of jobs
$11
$20
$33
How much do trainee agent based modeling jobs pay per hour?
As of May 31, 2026, the average hourly pay for trainee agent based modeling in the United States is $20.64, according to ZipRecruiter salary data. Most workers in this role earn between $16.83 and $21.88 per hour, depending on experience, location, and employer.
What are the most commonly searched types of Agent Based Modeling jobs? The most popular types of Agent Based Modeling jobs are:
Full-time
Posted 9 days ago
Job description
Description
The Department of Radiology Clinical Research Division invites applications for an Associate Research Scientist to join the Center for Advanced Diagnostic Research (CADRe) of Dr. Stella Kang. The successful candidate will lead the development and implementation of advanced computational models of disease, with a focus on oral lesions and cancers.
This position involves the design, execution, and analysis of quantitative disease simulation models, including state-transition (Markov) models, discrete event simulations, differential equations, and agent-based modeling approaches. The candidate will integrate epidemiologic and clinical data from national datasets and the scientific literature into robust computational frameworks.
Specific duties include:
Qualifications
Minimum Qualifications:
Preferred Qualifications:
The Department of Radiology Clinical Research Division invites applications for an Associate Research Scientist to join the Center for Advanced Diagnostic Research (CADRe) of Dr. Stella Kang. The successful candidate will lead the development and implementation of advanced computational models of disease, with a focus on oral lesions and cancers.
This position involves the design, execution, and analysis of quantitative disease simulation models, including state-transition (Markov) models, discrete event simulations, differential equations, and agent-based modeling approaches. The candidate will integrate epidemiologic and clinical data from national datasets and the scientific literature into robust computational frameworks.
Specific duties include:
- Design, develop, and validate computational disease models using state-transition, discrete event, differential equation, and agent-based modeling methodologies.
- Implement simulation models in Python, R, C, C++, or other scientific programming environments.
- Integrate model parameters using national datasets for incidence, mortality, and related epidemiologic outcomes.
- Conduct structured literature reviews to inform model inputs, assumptions, and validation.
- Apply principles of diagnostic test accuracy, including ROC analysis.
- Perform statistical analyses, including multivariable regression and time-to-event methods, as needed to support modeling.
- Develop and maintain databases of model inputs, outputs, and analytical results.
- Prepare manuscripts, abstracts, and presentations for peer-reviewed journals and scientific conferences.
- Present regular progress updates to the Principal Investigator and collaborate with a multidisciplinary research team.
- Mentor junior researchers, including Postdoctoral Fellows and research assistants, as appropriate.
Qualifications
Minimum Qualifications:
- Ph.D. in decision sciences, industrial engineering, epidemiology, biostatistics, mathematics, engineering, computational sciences, or a related quantitative field.
- Demonstrated expertise in simulation modeling methodologies, including Markov/state-transition, discrete event, differential equation, and/or agent-based modeling.
- Strong foundation in probability theory and statistical methods.
- Proficiency in scientific programming (Python, R, C, C++, or equivalent).
- Experience conducting systematic literature searches using PubMed/MEDLINE, Embase, or similar databases.
- Excellent written and oral communication skills in a scientific context.
- Strong organizational skills for managing complex datasets and multi-component modeling projects
Preferred Qualifications:
- Experience in decision analytic modeling or economic evaluation.
- Knowledge of epidemiologic methods and health outcomes research.
- Prior involvement in modeling cancer or oral lesion progression.
- Experience mentoring trainees and collaborating within multidisciplinary research teams.
About Columbia | SIPA
Sourced by ZipRecruiter
Industry
Colleges, universities, and professional schools
Company size
201 - 500 Employees
Headquarters location
New York, NY, US
Year founded
1947