Project Overview
Mens, Manus and Machina (M3S) Interdisciplinary research group (IRG) at Singapore-MIT Alliance for Research and Technology (SMART) invites applications for a Postdoctoral Associate in Generative AI and Human Capital Development. This ambitious project seeks to redefine how we understand, simulate, and optimize career decisions in a dynamic job market. Successful candidates will bridge the fields of Generative AI, Recommendation System, Labor Economics/Organizational Science, and Social Simulation Platform. The key focus areas of this project include:
1. Agentic Career Recommendation Systems
Build LLM-based agent systems for personalized career recommendation that operate over long-term user memory, structured experience representations, and continual information retrieval, enabling recommendations that evolve with an individual’s goals, constraints, and market conditions over time.
2. LLM-Agent Simulation for Organizational Modeling
Design multi-agent simulation environments using LLMs to model organizational dynamics, including role differentiation, collaboration and competition, culture formation, and decision propagation within and across organizations.
3. Career Understanding via Counterfactual & Causal Modeling
Develop causal and counterfactual modeling frameworks with LLMs to understand career transitions, disentangle skill, opportunity, and structural factors, and simulate long-horizon “what-if” career trajectories under alternative decisions and environments.
The M3S-T4 team is led by distinguished scholars, Professors Jinhua Zhao, Paul Liang from MIT, Professor Shenhao Wang from University of Florida, and Professor Archan Misra from Singapore Management University.
Responsibilities
- Collaborate with the project team and other researchers to design, implement, and evaluate research projects.
- Publish research results in top-tier journals and conferences and disseminate research findings through presentations and other means.
- Mentor graduate and undergraduate researchers and interns involved in related projects.
- Assist with grant writing, project management, and other administrative research duties.
- Perform other duties as needed.
Requirements
- Ph.D. in Computer Science, Artificial Intelligence, Data Science, Automation, Electronic Engineering, Economics, Human Resources Management, or a related field.
- Experience with general methods in machine learning, such as reinforcement learning, deep learning, generative AI, multimodal AI, statistical modeling, and network analysis.
- Preferred experience in the following areas: Recommendation System, LLM alignment, LLM agent system, Causal Discovery and Inferencing using AI.
- Strong publication record in top-tier conferences and journals.
- Excellent communication and collaboration skills.
Interested applicants are invited to send in their full CV/resume, cover letter and list of three references (to include reference names and contact information). We regret that only shortlisted candidates will be notified.
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