The Complex Systems Science team at the College of Science, School of Physical and Mathematical Sciences, led by A/Prof Cheong Kang Hao, is looking for passionate individuals to join its interdisciplinary research team.
Vacancy: Research Fellow (AI Scientist) – Educational AI, Learning Analytics, and Immersive Simulation
The Research Fellow will lead and support AI and data science workstreams across a portfolio of projects, with an initial focus on building AI-driven learning analytics for immersive virtual laboratory simulations and personalized assessment.
Key responsibilities:
AI and data science development
Design, develop, and validate machine learning models for skill inference, mastery estimation, and personalized feedback, including Bayesian approaches, sequence models (for example LSTM), and reinforcement learning where appropriate.
Engineer data pipelines to capture, clean, and analyze high-frequency interaction telemetry (for example accuracy, reaction time, and action sequences) and generate individual learning trajectory reports.
Build evaluation frameworks to benchmark AI outputs against expert-defined competence standards and human ratings; implement active learning loops with domain experts.
Productization and platform engineering
Develop analytics services, dashboards, and reporting tools for educators and learners, with attention to usability, privacy, and auditability.
Implement MLOps practices (versioning, reproducible training, model monitoring, data governance) suitable for research-to-deployment pathways.
Integrate AI components with XR or simulation platforms (for example Unity-based workflows), including instrumentation for event logging and performance analytics.
Co-design study protocols with investigators, including quasi-experimental designs, and support statistical analysis and interpretation of learning outcomes.
Stakeholders and other contributions
Contribute to publications, technical reports, and research dissemination/presentation; support grant reporting and documentation.
Identify opportunities to reuse models, pipelines, and analytics modules across other domains and projects (for example healthcare, training, serious games, and adaptive learning).
Work closely with stakeholders to translate requirements into AI specifications and deliverables.
Mentor research assistants and student project members; review code, support experimentation, and enforce good research engineering practices.
Job Requirements:
PhD in Computer Science, AI, Electrical Engineering, Biomedical Engineering, Mathematical Sciences, Informatics, Control, or related disciplines.
Strong background in AI, deep learning, and data analytics.
Experience with multimodal data integration and analysis.
Proficiency in programming languages such as Python, MATLAB, or R.
Experience with signal processing and statistical analysis.
Knowledge of neurophysiological assessment techniques and behavioral analysis.
Strong publication record.
Excellent problem-solving skills and ability to work independently and collaboratively.
Effective communication skills for interdisciplinary collaboration and dissemination of research findings.
We regret that only shortlisted candidates will be notified.
Hiring Institution: NTU