We are seeking talented individuals for the position of Research Fellow. We welcome applicants with a doctoral degree (PhD) for the Research Fellow position in various backgrounds such as experimental psychology, biopsychology, cognitive psychology, educational neuroscience, NeuroAI, neuropsychology, neurology, psychiatry, cognitive neuroscience, and related fields. You will be an integral member of an inter-disciplinary Science of Learning research team in developing brain-based machine-learning predictive models for early identification of mathematical learning difficulties in kindergarten and early primary level students.
The successful candidate will play a key role in a multidisciplinary research project aimed at the early identification of mathematical learning difficulties in young children. The position involves supporting the day-to-day coordination of the project, conducting data collection with children, and contributing to the development of machine learning and deep learning models for early prediction. The research integrates behavioural and cognitive assessments with neuroimaging and AI, including neuropsychological testing, cognitive tasks, functional Magnetic Resonance Imaging (fMRI), structural MRI, and predictive modelling approaches. As the assessment tools have already been established and implemented, the project is now at an exciting stage focused on high-quality data collection, data management, and subsequent AI-driven analysis. The role is well suited for a candidate who is organised, detail-oriented, adaptable, and able to work both independently and collaboratively, with strong interpersonal skills and confidence in engaging young children in a research setting.