First seen by our source: 1 hour ago
Lecturer (Data Literacy)
@ NUS Centre for Cancer Research (N2CR) | NUS Medicine
Provost, Alberta
Overview
The National University of Singapore is hiring a Lecturer in Data Literacy on a full-time, renewable contract under its Educator Track scheme. The role assists the Course Lead in refining and delivering GEA1000 Quantitative Reasoning with Data, a university-wide course on data sense-making and visualisation. A PhD in a quantitative discipline is required, with start in semester 1 of AY2026/2027.
Responsibilities:
- Assist Course Lead in refining GEA1000 content, delivery and assessment
- Integrate AI and other technologies into teaching pedagogies
- Align course with higher-level data science and analytics courses
Requirements summary:
- PhD in Statistics, Mathematics, Physics or closely related quantitative discipline
- Proficiency in Excel, Python or R
- Proven track record teaching broad undergraduate courses
- Experience in course design and assessment development
Tools & skills
Source and dates
Source type not verified · apify-linkedin
- Employer posting date
- Not provided
- First seen by our source
- 2026-11-15
- Source record updated
- 2026-11-15
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Entry level |
| Department | Education |
| Hours per week | 40 (estimated) |
| Work setting | Office |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
| Education | Doctorate (required) |
| Fields of study | Statistics, Mathematics, Physics, Quantitative disciplines |
Summary and details written by AI from the posting; the employer’s posting is the authority.
NUS Centre for Cancer Research (N2CR) | NUS Medicine
| Field | Value |
|---|---|
| Open jobs on Jobsy | 1 |
Apply now
Lecturer (Data Literacy)
University-Level Unit:
Office of the Provost
Faculty/Department-Level Unit:
General Education Unit
Employee Category:
Other Teaching Staff
Job Title: Lecturer (Data Literacy)
University-Level Unit: Office of the Provost
Faculty/Department-Level Unit: General Education Unit
Employee Category: Other Teaching Staff
Location_ONB: Kent Ridge Campus
Posting Start Date: 21/08/2026
Job Description
Position Overview
Applications are invited for the post of Lecturer in Data Literacy at the National University of Singapore (NUS). The successful candidate will be appointed on a full-time, renewable contract under the NUS Educator Track scheme. The post is hosted by the Office of the Provost as administrative host and incubator for the programme, in collaboration with the Department of Mathematics and the Department of Statistics and Data Science.
Key Responsibilities
- Curriculum Design & Delivery: Assist Course Lead in directing the ongoing refinement of content, delivery and assessment for the university-wide general education course for the AI era, GEA1000 Quantitative Reasoning with Data. The course introduces foundational data sense-making and visualisation, drawing on authentic datasets from diverse fields, including science and engineering, healthcare, consumer insights, and public policy.
- Educational Innovation: Assist the Course Lead in integrating AI and other technologies into teaching pedagogies to enhance student mastery of core data concepts.
- Curriculum Alignment: Assist the Course Lead in collaborating with academic units across the university to ensure integration between this course and the higher-level data science and analytics courses.
Start date: Immediate, or as soon as practicable, in semester 1 of AY2026/2027
Qualifications
Qualifications and Requirements
Essential
- PhD in Statistics, Mathematics, Physics, or closely related quantitative discipline.
- Technical Proficiency: Demonstrated expertise in data science, analytics, and practical applications, including proficiency in Excel, and programming languages such as Python or R.
- Higher Education Teaching: Proven track record of delivering broad-based, common curriculum undergraduate courses.
- Curriculum Development: Experience in course design, assessment development, and programmatic alignment.
- Pedagogical Innovation: Experience in leveraging educational technologies, including generative AI, for innovative teaching pedagogies to enhance learning outcomes.
- Scholarship of Teaching & Learning: Active interest or experience in evidence-based pedagogical research.
- Cover letter
- Curriculum vitae
- Scanned copies of academic degrees
- Teaching statement
- Two academic or professional referee letters
Apply now
Lecturer (Data Literacy)
Key Responsibilities
- Curriculum Design & Delivery: Assist Course Lead in directing the ongoing refinement of content, delivery and assessment for the university-wide general education course for the AI era, GEA1000 Quantitative Reasoning with Data. The course introduces foundational data sense-making and visualisation, drawing on authentic datasets from diverse fields, including science and engineering, healthcare, consumer insights, and public policy.
- Educational Innovation: Assist the Course Lead in integrating AI and other technologies into teaching pedagogies to enhance student mastery of core data concepts.
- Curriculum Alignment: Assist the Course Lead in collaborating with academic units across the university to ensure integration between this course and the higher-level data science and analytics courses.
Start date: Immediate, or as soon as practicable, in semester 1 of AY2026/2027
Essential
- PhD in Statistics, Mathematics, Physics, or closely related quantitative discipline.
- Technical Proficiency: Demonstrated expertise in data science, analytics, and practical applications, including proficiency in Excel, and programming languages such as Python or R.
- Higher Education Teaching: Proven track record of delivering broad-based, common curriculum undergraduate courses.
- Curriculum Development: Experience in course design, assessment development, and programmatic alignment.
- Pedagogical Innovation: Experience in leveraging educational technologies, including generative AI, for innovative teaching pedagogies to enhance learning outcomes.
- Scholarship of Teaching & Learning: Active interest or experience in evidence-based pedagogical research.
- Cover letter
- Curriculum vitae
- Scanned copies of academic degrees
- Teaching statement
- Two academic or professional referee letters
Journal
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