Teaching Assistant, Undergraduate Education
QUANTITATIVE REASONING WITH DATA MODULE AT NATIONAL UNIVERSITY OF SINGAPORE
Applications are invited for the position of Teaching Assistant/Instructor in the module GEA1000 Quantitative Reasoning With Data, which is compulsory for almost all first-year undergraduates. It aims to cultivate a critical attitude towards quantitative information and arguments in mass media and to equip students with basic data manipulation and visualization skills.
Duties include facilitation of classroom discussion, student consultation, supervision of group projects, designing teaching materials and design of assessment tasks. Successful candidates are expected to commit to two years of full-time service.
Start date: By 29 July 2022
Bachelor or Master degree, preferably with experience in teaching or practicing empirical quantitative work.
- Competence in interpreting and communicating numerical information.
- Interest in academic interaction with adults from all disciplines.
- Being proactive and reflective about teaching practice.
- Competence in a data analysis software, such as EXCEL or R.
Please attach CV and all university education transcripts. Only shortlisted applicants will be notified.
At NUS, the health and safety of our staff and students are one of our utmost priorities, and COVID-vaccination supports our commitment to ensure the safety of our community and to make NUS as safe and welcoming as possible. Many of our roles require a significant amount of physical interactions with students/staff/public members. Even for job roles that may be performed remotely, there will be instances where on-campus presence is required.
Taking into consideration the health and well-being of our staff and students and to better protect everyone in the campus, applicants are strongly encouraged to have themselves fully COVID-19 vaccinated to secure successful employment with NUS.
Location: Kent Ridge Campus
Organization: Office of the Sr Dy President & Provost
Department : Undergraduate Education
Employee Referral Eligible: No
Job requisition ID : 16344