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Massachusetts Institute of Technology
Top university
4 days ago
Postdoctoral Associate in Applied AI for Investment Decisions Massachusetts Institute of Technology in United States
Degree Level
Postdoc
Field of study
Computer Science
Funding
The 12-month appointment is renewable subject to funding and performance. Salary is competitive and at or above the MIT postdoctoral minimum, with full MIT benefits. The stated salary range is $73,308-$90,000.
Country
United States
University
Massachusetts Institute of Technology
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About this position
The Massachusetts Institute of Technology is seeking a Postdoctoral Associate in Applied AI for Investment Decisions to join a research program at the MIT Sloan School of Management in Cambridge, Massachusetts. The project investigates how artificial intelligence systems can be built, evaluated, and deployed in large-scale investment decisions that require synthesizing financial statements, diligence reports, management materials, market data, and other heterogeneous evidence.
Funded by the MIT Generative AI Impact Consortium in partnership with a leading global investment firm, the research uses historical private-market investment records and realized outcomes to examine whether AI models identify the information that genuinely drives investment decisions. The program will study when AI systems add decision value, how their information use can be measured, and where they fail.
The postdoctoral researcher will work with Professor Eric So on applied AI research involving the evaluation and probing of large language models in high-stakes decision settings. The role leads the technical development of benchmark instances from confidential diligence records, including point-in-time controls, document and claim-level parsing, and fixed outcome definitions. The researcher will implement selector–forecaster evaluation pipelines, apply proper scoring rules, and conduct sufficiency and comprehensiveness tests against random-subset and no-document baselines.
Additional work includes matching claims against investment committee records, comparing document-type baselines, systematically probing frontier models through their APIs, and designing ablation and perturbation experiments. The postdoctoral associate will also investigate memorization and recognition leakage, manage reproducibility and model API constraints, co-author academic papers, prepare practitioner-facing summaries, and present findings at consortium, partner, and academic meetings.
The researcher will be part of an interdisciplinary environment connecting machine learning, economics, finance, empirical research, and investment practice. The position also includes helping supervise research assistants working on annotation and data projects.
Funding details
The 12-month appointment is renewable subject to funding and performance. Salary is competitive and at or above the MIT postdoctoral minimum, with full MIT benefits. The stated salary range is $73,308-$90,000.
What's required
Applicants must hold a PhD in computer science, economics, or finance completed by the start date. Economics and finance candidates should demonstrate a clear orientation toward machine learning and applied AI research through papers, code, or projects. Strong Python programming skills and experience building reproducible empirical or machine-learning pipelines are required, as is hands-on experience running large language model experiments through model APIs. Applicants must be able to work independently and handle confidential data under a data-use agreement. Preferred qualifications include experience with systematic LLM probing, evaluation harnesses, log-probability or calibration analysis, input ablation or perturbation, benchmark or evaluation design, retrieval and attribution, rationale evaluation, forecasting and scoring rules, financial statements, valuation, investment decision-making, and research publications or strong working papers.
How to apply
Submit a CV, a one-page cover letter describing relevant research and LLM experience, one or two writing samples or research papers, optional code repository links, and the names and contact information of two or three references. Applications are reviewed on a rolling basis until the position is filled.
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