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.