Massachusetts Institute of Technology

Postdoctoral Associate, AI-Powered Testing for Dynamic Models of Social Systems

Education, Government & Non-Profit
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Ph.D. or equivalent doctoral degree in system dynamics, computer science, or related field.
  • Strong programming skills for developing and maintaining research software.
  • Ability to translate ambiguous research goals into actionable tasks.
  • Demonstrated competence in designing and executing computational research.
  • Experience working independently and making technical decisions.

Responsibilities

  • Design and codify model confidence-building tests into a machine-readable taxonomy.
  • Implement and iterate on a test-generation pipeline using LLM/RAG techniques.
  • Generate and maintain code for various model testing workflows.
  • Evaluate AI-generated tests against expert-designed benchmarks.
  • Disseminate project outputs through open-source releases and presentations.

Benefits

  • Opportunity to work at MIT, known for its innovative research environment.
  • Collaboration with leading experts in the field, providing networking opportunities.
  • Independent work culture promoting self-directed research.
  • Exposure to diverse modeling projects across urban dynamics and sustainability.
  • Contributions to open-source software, enhancing professional visibility.
Full Job Description
Description

The MIT Sloan School of Management seeks a full-time Postdoctoral Associate to lead research software development and evaluation for a MGAIC-funded project led by Prof. Hazhir Rahmandad on AI-powered testing for dynamic models of social systems. The project will build an open-source pipeline using large language models, retrieval-augmented generation, and software-testing methods to generate, prioritize, implement, and continuously run quality-assurance tests for system dynamics and related simulation models.

The position is intended for a high-agency researcher-builder who can work independently to move from research design to working prototypes, evaluate the pipeline on benchmark models, and disseminate outputs through open-source software, publications, presentations, and SERC community activities.

Principal Duties and Responsibilities (Essential Functions**)

- 20% - Research design and test taxonomy. Codify model confidence-building tests into a machine-readable taxonomy; define benchmarks and test specifications for approximately a dozen smaller literature models and two complex test beds, including urban dynamics and climate/sustainability models; exercise independent judgment in scoping, prioritizing, and translating qualitative model-quality concepts into measurable checks.

- 25% - LLM/RAG test-generation pipeline. Design, implement, and iterate prompts, retrieval workflows, model parsers, and orchestration code that generate prioritized tests from natural-language problem statements and from working models and datasets; make independent technical decisions about architecture, evaluation metrics, error handling, and reproducibility.

- 25% - Executable testing and continuous integration. Generate and maintain code to execute structural, behavioral, dimensional, extreme-condition, sensitivity, and data-fit tests in model workflows; develop interfaces for Vensim, XMILE, SDEverywhere, and extensible Python/JavaScript tools; create repeatable continuous-monitoring workflows that flag regressions after model changes.

- 15% - Evaluation and validation. Compare AI-generated tests against expert-designed benchmark tests; analyze false positives, false negatives, novelty, and usefulness; conduct and document structured feedback sessions with lead modelers and domain experts; maintain reproducible datasets, analysis scripts, and results.

- 10% - Dissemination and project leadership. Prepare an open-source release, technical documentation, manuscripts, conference submissions, presentations, and final reports; participate in SERC programming and lead or organize a SERC Scholar Group during the academic year; coordinate with MIT/SERC collaborators and external modeling communities.

- 5% - General collaboration and administrative duties. Contribute to project planning, version control, issue tracking, code review, meetings, and informal mentoring of students or assistants on project-specific tasks as needed.

Other duties as needed or required.

Supervision Received

Reports to Prof. Hazhir Rahmandad, MIT Sloan School of Management. Receives general supervision with regular one-on-one meetings and milestone reviews. The Postdoctoral Associate is expected to exercise a high level of independent judgment in research design, technical architecture, implementation, evaluation, and day-to-day prioritization, while coordinating with the PI on scientific direction, publication decisions, project milestones, and external commitments.

Supervision Exercised

No formal supervisory responsibility. The Postdoctoral Associate may provide technical guidance, code review, and day-to-day mentoring to graduate or undergraduate research assistants or collaborators on project-specific tasks. This role is not expected to make hiring, salary, disciplinary, or formal performance-review decisions.

Qualifications

Qualifications & Skills

MINIMUM REQUIRED EDUCATION AND EXPERIENCE:

- Ph.D. or equivalent doctoral degree by start date in system dynamics, computer science, software engineering, computational social science, operations research, or a related field.

- Strong programming skills to build, test, document, and maintain reusable research software.

- Demonstrated ability to design and execute computational research; work with simulation models, data, or scientific code; and translate ambiguous research goals into implementable tasks.

- Ability to work independently, make sound technical decisions, manage multiple workstreams, and communicate progress, risks, and results clearly.

PREFERRED EDUCATION AND EXPERIENCE:

- Experience with system dynamics, agent-based modeling, social simulation, computational social science, model validation/testing, causal or feedback modeling, or policy modeling.

- Experience with large language models, retrieval-augmented generation, prompt orchestration, evaluation of AI-generated code or scientific outputs, or trustworthy AI methods.

- Experience with automated software testing, test-driven development, continuous integration, Git/GitHub, containers, or open-source software maintenance.

- Experience with Vensim, XMILE, SDEverywhere, NetLogo, Stella, AnyLogic, PySD, or related modeling and simulation tools.

- Evidence of high-agency research software development, such as a public code repository, deployed tool, package, reproducible workflow, or substantial technical artifact.

** To comply with regulations by the Americans with Disabilities Act (ADA), the principal duties in position descriptions must be essential to the job. A job function is essential if removal of that function would fundamentally change the job. The essential functions above focus on the purpose and result of the duties rather than the manner in which they are performed.

Application Instructions

Please provide the following compiled in one attachment:

1. Cover letter describing your fit with the project

2. CV

3. Research statement of primary research interests

Hiring Pay Range: $73,308-$90,000

About Massachusetts Institute of Technology

The Massachusetts Institute of Technology (MIT) is a private research university located in Cambridge, Massachusetts. MIT is a member of the Association of American Universities (AAU) and is classified among "R1: Doctoral Universities – Very high research activity". The university is known for its strong emphasis on scientific and technological research and its engineering programs. MIT was founded in 1861 and has a long history of innovation and entrepreneurship. The university has produced numerous Nobel laureates, Rhodes Scholars, and MacArthur Fellows.
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