New Ph.D. positions available in Learning Analytics [Jan 2025 or Aug 2026 intake]. |
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Recommendation systems have become a key area of research in recent years with applications such as e-commerce, movies, and education. While course recommendation systems for the education sector has been the research focus in recent years, these systems rely mainly on academic performance and interest of the students. More recently, driven by the push toward skills-based employment, there is an urgent need to develop a new paradigm toward course recommendation systems. The goal of this research is to develop course recommendation machine learning architecture based on skills and competencies acquired by students during their undergraduate degree. This recommendation system will allow the student to pursue relevant courses that are aligned with their existing skills as well as gaps that, in turn, will allow them to deepen their skills and/or competencies for them to contribute effectively to their respective organizations upon graduation. Ph.D. candidates interested to embark in this exciting research should have an engineering degree in related field (Electrical & Electronic and/or Computer Engineering). They must be proficient in Python and, in particular, implementing machine learning models, training them, and validating their performance. They are expected to develop new machine learning architectures and deploying the developed models in an actual academic environment. This resarch is supervised by A/P Andy Khong and Prof. Tan Ooi Kiang. For application and enquiries please contact A/P Andy Khong at andykhong@ntu.edu.sg |
Student mental health poses a great societal challenge. The World Health Organization's World Mental Health Surveys found that 20% to 31% of college students experience diagnosable mental disorders. In Singapore, one in three youths report mental health symptoms, including sadness, anxiety, and loneliness. The goal of this research is to develop predictive models for mental wellness using digital biomarkers extracted from wearable devices. Working with a team of researchers from the Lee Kong Chian School of Medicine, the Ph.D. candidate will examine student's digital biomarkers longitudinally and develop machine learning algorithms to predict mental health issues within the context of Nanyang Technological University, Singapore. Ph.D. candidates interested to embark in this exciting research should have an engineering degree in related field (Electrical & Electronic and/or Computer Engineering). They must be proficient in Python and, in particular, implementing machine learning models, training them, and validating their performance. They are expected to develop new machine learning architectures and deploying the developed models in an actual academic environment. This resarch is supervised by A/P Andy Khong and Prof. Tan Ooi Kiang. For application and enquiries please contact A/P Andy Khong at andykhong@ntu.edu.sg |