Research Assistant, Learning Analytics Specialist
The Lead Principal Investigator of a high-profile, joint adult education research project between NUS and Cisco Systems, is looking to hire a Research Assistant to join the research team as a Learning Analytics Specialist. The goal of this project to optimize the training of professionals for Industry 4.0 and in turn raise workforce productivity by leveraging learning and business analytics. Specifically, the “final product” will be a productivity-driven, physical-digital training ecosystem that delivers heutagogical (or self-directed) learning experiences seamlessly across different settings such as individual versus social learning and formal versus informal learning, to support different types of adult learners and learning behaviours. The brain of this novel learning environment will be a recommendation system that studies longitudinal data comprising professionals’ evolving skills set, career progression, individual and business unit productivity metrics, and talent management practices, and predicts training needs when new information is supplied. Successful candidates will be affiliated to the new Cisco-NUS Accelerated Digital Economy Corporate Laboratory. The duration of the project is five years. Successful candidates will initially be hired on a two-year contract which may be subsequently renewed (subject to satisfactory performance).
Contribute to the research team in the following areas:
- security, privacy and confidentiality of research data
- development of surveys and other instruments for research purposes
- data collection (through surveys, focus group discussions, interviews, Cisco’s proprietary platform for teamwork, NUS’s learning management system, etc.), including documentation of collected data
- construction and maintenance of datasets, analysis of data, modelling, and reporting
- prototyping and testing
- Bachelor’s or Master’s degree in STEM or related discipline (with preference for Engineering, Computer Science, Statistics, or Data Analytics).
- Experience in building and maintaining datasets.
- Knowledge of statistical methods and data mining techniques as well as proficiency in a language suitable for advanced data analytics such as Python or R.
- Specialized knowledge in one or more of the following will be an advantage:
- social-network graph mining,
- text mining.
- Excellent technical writing and presentation skills.
- Analytical, resourceful and a team-player.
- High levels of integrity for responsible conduct of research and stewardship of data.
Location: Kent Ridge Campus
Department: Biomedical Engineering
Employee Referral Eligible: No
Job requisition ID: 7845