The Complex Systems Science Group 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 as a Research Fellow.

Despite advocacy for early detection and screening in Autistic Spectrum Disorders (ASD), there remains a significant gap between service need and current technology and implementation. This project aims to bridge this gap by developing a novel multimodal neurophysiology-behavioral assessment device for studying ASD in early childhood. Our goal is to integrate multiple virtual and real-life stimuli and task designs with a multi-modality sensor array, including electroencephalogram (EEG), functional near-infrared spectroscopy (fNIRS), eye-tracking, facial expression and behavior tracking, among others. In response, we are seeking to hire a Research Fellow (AI Scientist) to support us in developing advanced AI techniques for data integration and real-time analysis, designing novel assessment protocols, and ensuring the seamless implementation of this innovative device for early ASD detection and assessment.

Key Responsibilities:

• Conduct cutting-edge research in the development of AI techniques for integrating multimodal data (EEG, fNIRS, eye-tracking, etc.).

• Design and implement novel assessment designs and stimuli for early childhood ASD studies.

• Develop and test AI-driven models for real-time data analysis and interpretation.

• Collaborate with interdisciplinary teams, including neuroscientists, engineers, and clinical experts.

• Publish research findings in high-impact journals and present at conferences.

Job Requirements:

• PhD in Computer Science, Electrical Engineering, Biomedical Engineering, Mathematical Sciences, Informatics, Neuroscience, or related fields.

• 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 to inform that only shortlisted candidates will be notified.