Job Description

The Lead Principal Investigator of a high-profile, joint adult education research project between NUS and Cisco Systems, is looking to hire a Research Fellow to join the research team as a Data Scientist. The goal of this project is to revolutionize the training of professionals for Industry 4.0 by leveraging big data to raise productivity. The “final product” will be a physical-digital training ecosystem that delivers self-determined learning experiences seamlessly across different settings to support different learning styles. The brain of this novel training environment will be an algorithm that studies longitudinal data comprising professionals’ evolving skills set, career progression and other inputs to predict training needs. The successful candidate will be affiliated to the new Cisco-NUS Accelerated Digital Economy Corporate Laboratory and will lead the research team in identifying the skills that professionals need for Industry 4.0, including the development of the aforementioned algorithm. He or she will also be expected to support the development of novel input quality measures for firm-level production functions. The duration of the project is five years. The successful candidate will initially be hired on a two-year contract which may subsequently be renewed (subject to satisfactory performance).

Key Responsibilities

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, including robust documentation of collected data.
• Construction and maintenance of datasets, analysis of data, modelling, and reporting.
• Supervision of junior research team members (i.e., research assistants)

Qualifications

• PhD in STEM or another discipline relevant to the project (with preference for Engineering, Computer Science, Statistics, Data Analytics/Science).
• Experience in building and maintaining datasets (with preference for educational 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.
• Experience in one or more of the following would be advantageous:
  • Neural networks and text mining.
  • Nonlinear regression and analysis of data related to firm-level production functions.
  • System integration and interoperability.
• 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.
   

More Information

Location: Kent Ridge Campus
Organization: Engineering
Department : Biomedical Engineering
Employee Referral Eligible: No
Job requisition ID : 10296