Research Associate (AI in Education)

SPMS is a School under NTU College of Science. Our School is organized into two divisions: the Division of Mathematical Sciences and the Division of Physics and Applied Physics. We are home to internationally-renowned research groups pursuing cutting-edge research in a diverse range of topics in the mathematical sciences, physics, and related disciplines.

For more details, please view School of Physical and Mathematical Sciences | NTU Singapore

We are seeking talented individuals for the position of Research Associate. We welcome applicants with a Master's degree (for the Research Associate position) in education, learning sciences, educational technology, computer science, artificial intelligence, data science, and related fields. Candidates who combine a background in education with hands-on experience in AI, or vice versa, are especially encouraged to apply. You will be an integral member of an inter-disciplinary Science of Learning research team investigating how generative AI can foster higher-order thinking among secondary school students.

The successful candidate will play a key role in a funded project that brings together educational research and AI technology. The project builds 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. Grounded in learning sciences and pedagogy, it examines when and how AI-supported dialogue strengthens students' reasoning, creativity and argumentation through classroom studies in partner schools, before scaling up across more schools. As the project is at an early stage, the successful candidate will have the opportunity to shape both the system and the study design. The role suits a candidate who is organised, adaptable, and comfortable working at the interface of education and AI, both independently and collaboratively.

Key Responsibilities:

• Conduct independent research.
• Handle grant-related administrative tasks (e.g., prepare and amend 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 working on the project.
• 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 research findings through publications in education and AI venues, conference presentations and teacher-facing resources.
• Coordinate between and liaising with faculty, collaborators, and stakeholders from different disciplines
• Carry any other duties as required by PI and co-PI(s)

Job Requirements:

Qualifications

• Master's degree for the Research Associate position, in education, learning sciences, educational technology, computer science, artificial intelligence, data science, and related fields.

Competencies and Skills

• Excellent oral and written communication skills.
• Knowledge and experience in education or social science research methodologies, including experimental designs and statistical analysis (e.g., R, Python, SPSS).
• Proficient in programming (e.g., Python), with hands-on experience using large language models (e.g., prompt engineering, API-based development, retrieval-augmented generation).
• Familiarity with LLM-based agents, multi-agent systems, or methods for evaluating AI-generated outputs.
• Experience with research project management, and with supervising research staff and students
• Excellent organizational and project coordination skills, and able to work within tight deadlines.
• Self-motivated and self-directed, able to work independently to collect data, analyse data, and communicate findings.

Experiences

• Experience with applying AI to educational scenarios (e.g., educational chatbots, intelligent tutoring, LLM-based learner or teacher agents, educational simulation) will be preferred.
• Experience with conducting education research with students or teachers, or analysing dialogue and learning process data, will be preferred.
• Experience with academic publication and dissemination of research findings in education and/or AI venues will be preferred.

Knowledge

• Good knowledge of learning sciences and educational theories, particularly higher-order thinking, critical and creative thinking, and dialogic or Socratic teaching.
• Good or working knowledge of machine learning, natural language processing and generative AI.

We regret to inform that only shortlisted candidates will be notified.