We are excited to announce an opportunity at Nanyang Technological University, Singapore. We are looking for passionate individuals to join our inter-disciplinary Science of Learning research team between Psychology and the School of Physical and Mathematical Sciences.

SPMS is a School under NTU College of Science. Our School is organized into two divisions: the Division of Mathematical Sciences and the Division of Physics and Applied Physics. We are home to internationally-renowned research groups pursuing cutting-edge research in a diverse range of topics in the mathematical sciences, physics, and related disciplines.

For more details, please view School of Physical and Mathematical Sciences | NTU Singapore

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, AI in education, deep learning, biomedical engineering, computer science, 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

Key Responsibilities:

• Conduct independent research

• Handle grant-related administrative tasks (e.g., prepare and amend ethics documents)

• Conduct literature reviews, and prepare research progress reports and policy reports for stakeholders

• Supervise and lead a team of full-time and part-time research staff and undergraduate student assistants working on the project.

• Play a central role in coordinating and running of neuroimaging study

• Data collection from young children

• Develop and/or manage data analysis pipelines

• Coordinate between and liaising with faculty, collaborators, and stakeholders from different disciplines

• Carry any other duties as required by PI and co-PI(s)

Job Requirements:

Qualifications

• Doctoral degree (PhD) for the Research Fellow position in experimental psychology, biopsychology, cognitive psychology, educational neuroscience, NeuroAI, neuropsychology, neurology, psychiatry, cognitive neuroscience, AI in education, deep learning, biomedical engineering, computer science, and related fields.

Competencies and Skills

• Possess excellent oral and written communication skills to perform literature reviews and write progress and research reports.

• Knowledge and experience in social science research methodologies.

• Good statistical knowledge and skills, including familiarity with statistical analysis tools (e.g., SPSS, R, Jamovi and JASP).

• Familiarity with neuroimaging software (e.g., SPM, AFNI, FSL).

• Familiar with coding (e.g., in R, MATLAB, Python).

• Experience with research project management.

• Experience with supervising research staff and students.

• Excellent organizational skills, project coordination and administration skills (e.g., in data management and storage), and able to work within tight deadlines.

• Good leadership skills.

• Self-directed learner who can effectively picks up relevant skills as needed.

• Self-motivated, able to work independently to collect data, analyse data, and communicate findings.

Experiences

• Experience with conducting cognitive neuroscience and/or neuroimaging research with children and/or adults, especially using fMRI, will be preferred.

• Experience with resting-state fMRI and/or naturalistic fMRI analyses will be preferred.

• Experience with cognitive/neuropsychological assessment with children and/or adults will be preferred.

• Experience with dissemination of research findings (e.g., conference presentations and research reports) and academic publication processes will be preferred.

Knowledge

• Good knowledge of cognitive functions and cognitive neuroscience theories and techniques.

• Good or working knowledge of machine learning techniques.

We regret to inform that only shortlisted candidates will be notified.