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

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.