Research Associate (AI in Education)

About the role

The School of Physical and Mathematical Sciences (SPMS) at NTU College of Science is looking for a Research Associate to join an interdisciplinary Science of Learning team. The team investigates how generative AI can foster higher-order thinking among secondary school students. The successful candidate plays a key role in a funded project building a curriculum-aligned learning partner powered by large language models, centred on Socratic dialogue that guides students to generate ideas, check evidence, compare perspectives and reflect. The project is at an early stage, so the candidate will help shape both the system and the study design.

Key responsibilities

• Conduct independent research and handle grant-related administrative tasks such as preparing and amending ethics documents.
• Conduct literature reviews and prepare research progress reports and policy reports for stakeholders.
• Supervise and lead a team of full-time and part-time research staff and undergraduate student assistants.
• Translate pedagogical principles into the design of LLM-based dialogue systems and agents, and evaluate them.
• Design and conduct classroom-based studies, including randomised controlled trials, in partner schools.
• Collect and analyse learner-AI dialogue and learning process data, and develop and/or manage data analysis pipelines.
• Disseminate findings through publications, conference presentations and teacher-facing resources.
• Liaise with faculty, collaborators and stakeholders from different disciplines, and carry other duties requested by the PI and co-PIs.

Required profile

• Master's degree in education, learning sciences, educational technology, computer science, artificial intelligence, data science or related fields.
• Organised, adaptable and able to work independently and collaboratively at the interface of education and AI.
• Preferred: experience applying AI to education (chatbots, intelligent tutoring, LLM-based agents, simulations), education research with students or teachers, and academic publication.

Required skills

• Knowledge of education or social science research methods, including experimental designs and statistical analysis (e.g. R, Python, SPSS).
• Programming proficiency (e.g. Python) and hands-on use of large language models (prompt engineering, API-based development, retrieval-augmented generation).
• Familiarity with LLM-based agents, multi-agent systems and evaluation of AI-generated outputs.
• Project management and supervision experience.
• Good knowledge of learning sciences and educational theories, and good or working knowledge of machine learning, NLP and generative AI.