Postdoctoral Associate

Postdoctoral Associate (Generative AI and Education)Singapore-MIT Alliance for Research and Technology Centre – Kent Ridge 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 examining their pedagogical efficacy, impact in learning, and society . Key Focus Areas 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. 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. 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. Ethics and Responsible AI – Investigate issues of transparency, bias, privacy, and inclusion in AI-supported learning environments. Scholarly Dissemination – Publish findings in high-impact journals and conferences across AI, education, and human–computer interaction. Mentorship and Grant Development – Mentor graduate and undergraduate researchers and contribute to grant writing and proposal development. 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 lead projects that develop novel AI systems and evaluate their impact on cognition, pedagogy, and learning across K–12, higher education, and continuous education contexts. Your work will involve both technical development —such as 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. 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 compliance, protecting human research subjects and vulnerable populations. 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 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. Application To apply, please visit our website at: Interested applicants are invited to send in their full CV, cover letter, and list of three references (including reference names and contact information). We regret that only shortlisted candidates will be notified. #J-18808-Ljbffr