Postdoctoral Associate (Generative AI and Education)

Singapore-MIT Alliance for Research and Technology Centre; Singapore; On-site; SGD 70,000 - 90,000; Full time

Job summary

A leading research institution in Singapore is seeking a Postdoctoral Associate in Generative AI and Education. The successful candidate will integrate AI technologies into educational contexts, conducting empirical research to evaluate their effectiveness. This role involves collaboration with various disciplines, design of AI models, and contributions to high-impact publications. Ideal candidates will have a Ph.D. in relevant fields and experience in education technology and research methodologies.

Qualifications

• Ph.D. (or near completion) in Education or related field.
• Strong statistical analysis and programming skills.
• Demonstrated research experience in Education.

Responsibilities

• Lead projects on AI integration in education.
• Design and evaluate generative AI models.
• Conduct experimental studies to measure impact.

Skills

Research experience in Education and Learning Sciences

Statistical analysis

Programming skills (Python, R)

Communication skills

Education

Ph.D. in Education, Learning Sciences, Computer Science, Cognitive Science

Tools

IRB protocols

Job description

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 Education. This position is ideal for a scholar passionate about exploring how emerging artificial intelligence technologies can advance education and deepen our understanding of teaching and learning. Successful candidate will bridge the fields of AI development and education research, working closely with other AI researchers in M3S to contribute in both the creation of generative AI systems and examine their pedagogical efficacy, impact in learning, and society.

Key Focus Areas

1. Generative AI Development for Learning – Work with other AI researchers to design and prototype AI models (e.g., LLMs, multimodal systems) that support learning, assessment, and teaching practice.

2. Empirical Education Research – Conduct controlled experimental studies (e.g. mixed-methods), including classroom interventions and needs assessment explorations, to evaluate the educational impact of AI-based tools.

3. Interdisciplinary Collaboration – Partner with faculty and researchers in computer science, education, psychology, and learning sciences to co-design research programs and align technology development with educational theory.

4. Ethics and Responsible AI – Investigate issues of transparency, bias, privacy, and inclusion in AI-supported learning environments.

5. Scholarly Dissemination – Publish findings in high-impact journals and conferences across AI, education, and human–computer interaction.

6. Mentorship and Grant Development – Mentor graduate and undergraduate researchers and contribute to grant writing and proposal development.

7. Research Translation – Collaborate with practitioners and policymakers to translate research findings into scalable educational innovations aligned with local societal contexts.

Responsibilities

As a Postdoctoral Associate in Generative AI and Education, you will play a key role in advancing research on the integration of artificial intelligence into K–12, higher education and continuous education contexts. You will lead projects that develop novel AI systems and evaluate their impact on cognition, pedagogy, and learning.

Your work will involve both technical development—such as working with other AI researchers for fine-tuning models or building AI-powered educational tools—and empirical inquiry, including designing experimental protocols and analyzing learning outcomes. You will contribute to the design and evaluation of generative AI models that enhance instructional design, automate feedback, support lesson planning, and enable personalized learning experiences. You will also design empirical studies—ranging from controlled lab experiments to classroom-based field trials—to measure learning efficacy and engagement.

Working collaboratively with both AI developers and educational researchers, you will ensure that the systems designed are not only technically robust but also pedagogically meaningful and socially responsible. This position offers opportunities to collaborate in multidisciplinary teams, publish high-impact research, mentor students, and contribute to M3S’ portfolio of interdisciplinary AI-in-education initiatives.

Requirements

• Ph.D. (or near completion) in Education, Learning Sciences, Computer Science, Cognitive Science, or related field.

• Demonstrated research experience in Education and Learning Sciences, ideally with a focus on generative AI.

• Proven record of publications or projects in education technology, learning analytics, or human–AI interaction.

• Knowledge of learning theory, instructional design, and assessment methodologies.

• Experience designing and conducting quantitative, qualitative, or mixed-methods educational research.

• Mastery of IRB protocols and IRB compliance, protection of human research subjects, vulnerable populations, informed consent topics, data and safety monitoring.

• Strong statistical analysis and programming skills (e.g., Python, R, or equivalent).

• Experience collaborating with educators or educational institutions on applied research projects.

• Ability to bridge technical and pedagogical perspectives, translating between educational needs and algorithmic design.

• Excellent communication and academic writing skills.

Preferred Attributes

• Experience developing or evaluating generative AI tools (e.g., LLM-based tutoring systems, AI-assisted content creation, or adaptive assessment).

• Strong publication record in AI in Education (AIED), Learning at Scale, CHI, ICML, or similar venues.

• Familiarity with ethics, equity, and inclusivity in educational AI applications.

• Collaborative mindset suited to a multidisciplinary research environment.

To apply, please visit our website at: https://portal.smart.mit.edu/careers/career-opportunities

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.