Research Assistant: Learning Science & AI for Early Math

Nanyang Technological University

Singapore

On-site

SGD 47,000 - 60,000

Full time

14 days+
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Job summary

Nanyang Technological University (NTU) in Singapore invites applications for a Research Assistant to join an inter-disciplinary Science of Learning team between Psychology and the School of Physical and Mathematical Sciences. The role focuses on developing brain‑based machine‑learning predictive models to identify mathematical learning difficulties in young students.

The successful candidate will manage day-to-day project operations, conduct literature reviews, and support data collection and

Qualifications

  • Bachelor’s degree in a relevant field (psychology, neuroscience, biomedical engineering, or related).
  • Experience with cognitive neuroscience/neuroimaging is preferred.
  • Strong data management and statistical analysis skills required.
  • Familiarity with machine learning concepts and data pipelines is desirable.
  • Ability to work independently and in multidisciplinary teams.

Responsibilities

  • Oversee day-to-day operations of the research project on brain-based predictive models.
  • Conduct literature reviews and prepare progress and policy reports.
  • Coordinate neuroimaging studies and data analysis pipelines.
  • Develop and manage data analysis pipelines and ensure data integrity.
  • Organize regular meetings with collaborators and stakeholders.

Skills

Statistical analysis
Data management
Programming: Python
Programming: R
Programming: MATLAB
Neuroimaging
Cognitive neuroscience
Project coordination
Excellent communication

Education

BSc in psychology/biomedical engineering

Tools

SPSS
R
MATLAB
Python
SPM
AFNI
FSL

Job description

Nanyang Technological University (NTU) in Singapore invites applications for a Research Assistant to join an inter-disciplinary Science of Learning team between Psychology and the School of Physical and Mathematical Sciences. The role focuses on developing brain‑based machine‑learning predictive models to identify mathematical learning difficulties in young students.

The successful candidate will manage day-to-day project operations, conduct literature reviews, and support data collection and

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