Interdisciplinary Research Team Member
7 days ago
Our team is dedicated to developing brain-based machine-learning predictive models for early identification of mathematical learning difficulties in kindergarten and early primary level students. We believe that this research has the potential to make a significant impact on education and we are looking for a highly skilled and motivated Research Fellow to join our team.
Responsibilities:
The successful candidate will be responsible for conducting independent research, handling grant-related administrative tasks, conducting literature reviews, preparing research progress reports and policy reports for stakeholders, supervising and leading a team of full-time and part-time research staff, playing a central role in coordinating and running neuroimaging studies, developing and/or managing data analysis pipelines, coordinating between and liaising with faculty, collaborators, and stakeholders from different disciplines, and carrying any other duties as required by the Principal Investigator and Co-Principal Investigators.
Requirements:
The ideal candidate should have a PhD degree in experimental psychology, biopsychology, cognitive psychology, educational neuroscience, NeuroAI, neuropsychology, neurology, psychiatry, cognitive neuroscience, AI in education, deep learning, biomedical engineering, computer science, or related fields. Excellent oral and written communication skills, good command of the English language, knowledge and experience in social science research methodologies, good statistical knowledge and skills, familiarity with neuroimaging software, coding skills, experience with research project management and supervision of research staff and students, excellent organizational skills, project coordination and administration skills, good leadership skills, self-directed learner who can effectively pick up relevant skills as needed, self-motivated, able to work independently to collect data, analyse data, and communicate findings, experience with conducting cognitive neuroscience and/or neuroimaging research with children and/or adults, especially using fMRI, experience with resting-state fMRI and/or naturalistic fMRI analyses, experience with cognitive/neuropsychological assessment with children and/or adults, dissemination of research findings, academic publication processes, good knowledge of cognitive functions and cognitive neuroscience theories and techniques, and good or working knowledge of machine learning techniques are essential.
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