The Applications of Teaching and Learning Analytics for Students (ATLAS@NTU) and ECL (Experiential and Collaborative Learning Office) are centres within InsPIRE supporting the NTU education strategy 2025 in learning analytics and curriculum mapping for the benefits of all students at the university.
This position is responsible for sourcing, developing and testing appropriate algorithmic solutions for a learning analytics research of the university. The role would also be responsible for providing data literacy workshops and consultations to faculty and students. Together with the directors and other researchers, the role would be responsible in driving the successful pilot of the learning analytics research project.
Key Responsibilities
- Lead in the publication of the impact of learning analytics on the teaching and learning goals of the research grant
- Create fit-for-purpose datasets for learning analytics goals
- Source, test, develop and continuously refine machine learning and/or data mining algorithms for learning analytics applications relating to the learning analytics goals of the university
- Perform data cleaning and other quality checks
- Develop dashboards and other visualisation tools for intended users
- Collaborate with NTU schools/departments, external agencies and other universities on their research and development in relation to the learning analytics goals of the university
- Provide data interpretation and literacy training/consultancy to student and staff (together with learning analysts)
Job Requirements
- PhD in Data Science and related fields
- Deep knowledge in statistical, data mining, AI and machine learning algorithms
- Deep working knowledge of Python or R; Expert level knowledge of Java would be a plus
- Strong ability in translating user needs into data science problem and solution.
- Good ability in communicating data science models to non-data science audience using simple language
- Existing publications on the use of data science in higher education
- Experiences with tools such as Denodo, data science platforms, Cloud AI/ML technologies and Qliksense would be ideal
- Familiarity with the principles of explainable AI would be ideal
- Team player with strong ability and willingness to support other work areas of the department
We regret that only shortlisted candidates will be notified.