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Internship Agent Based Modeling Jobs (NOW HIRING)

Operations Research Analyst

El Segundo, CA ยท On-site

$215K - $250K/yr

... agent-based methods Develop and apply analytical models for cross-enterprise architecture studies, development plans, technology development efforts, and military utility studies Assess outcomes and ...

Using those models, predict future material properties and instrument performance and develop key insights to accelerate learning cycles and reduce the cost of empirical R&D. * Thoroughly document ...

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Internship Agent Based Modeling information

What is the difference between Internship Agent Based Modeling vs Internship Data Analyst?

AspectInternship Agent Based ModelingInternship Data Analyst
Required CredentialsRelevant coursework in modeling, programming, or simulation; sometimes a background in computer science or mathematicsDegree in statistics, mathematics, or related field; proficiency in data analysis tools
Work EnvironmentResearch labs, simulation environments, or industry settings focusing on modeling complex systemsBusiness, finance, healthcare, or tech companies analyzing data sets
Employer & Industry UsageUsed in research, government agencies, and industries requiring simulation of agent behaviorsCommon across various industries for decision-making and reporting

Internship Agent Based Modeling focuses on developing and analyzing simulation models of agents within complex systems, often requiring programming skills. In contrast, Internship Data Analysts primarily interpret and visualize data to support business decisions. Both roles involve data handling but differ in methods and application areas.

What is an Internship in Agent Based Modeling?

An Internship in Agent Based Modeling is a temporary position, typically for students or recent graduates, where you learn and assist in developing computational models that simulate the actions and interactions of autonomous agents. The role involves using programming and mathematical techniques to study complex systems in fields like economics, biology, or social sciences. Interns often work with simulation tools, analyze data, and contribute to research projects under the supervision of experienced modelers. This internship helps you gain practical experience in computational modeling and can enhance your understanding of how agent-based simulations are used to solve real-world problems.

What are the key skills and qualifications needed to thrive as an Internship Agent Based Modeling, and why are they important?

To thrive as an Internship Agent Based Modeling, you need a solid background in mathematics, computer science, or a related field, along with experience in modeling and simulation techniques. Familiarity with programming languages such as Python or Java, and tools like NetLogo, AnyLogic, or Repast, is typically required. Strong analytical thinking, problem-solving skills, and the ability to communicate complex concepts clearly are standout soft skills. These skills and qualities are crucial for developing accurate models, interpreting simulation results, and collaborating effectively within research or development teams.

What are the typical projects an intern in Agent-Based Modeling might work on, and how do they contribute to the team's goals?

As an intern in Agent-Based Modeling, you can expect to work on projects involving the simulation of complex systems, such as social networks, economic markets, or biological processes. Your tasks may include developing and testing models, analyzing simulation results, and assisting with data collection or visualization. These projects are integral to the team's research or product development goals, as your models help generate insights, validate hypotheses, and inform decision-making. Collaboration with data scientists, researchers, and software engineers is common, providing valuable exposure to interdisciplinary teamwork and real-world problem-solving.
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Associate Research Scientist

Associate Research Scientist

Columbia University in the City of New York

New York, NY โ€ข On-site

Full-time

Re-posted 23 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:
  • 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:
  1. Ph.D. in decision sciences, industrial engineering, epidemiology, biostatistics, mathematics, engineering, computational sciences, or a related quantitative field.
  2. Demonstrated expertise in simulation modeling methodologies, including Markov/state-transition, discrete event, differential equation, and/or agent-based modeling.
  3. Strong foundation in probability theory and statistical methods.
  4. Proficiency in scientific programming (Python, R, C, C++, or equivalent).
  5. Experience conducting systematic literature searches using PubMed/MEDLINE, Embase, or similar databases.
  6. Excellent written and oral communication skills in a scientific context.
  7. 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.