Part-Time Lecturer: Foundations of Data Science

Ref: SCU DS L0 1

• A completed Masters / M. Tech in Information Technology, Computer Science, Information Security, Information Systems, Statistics, Mathematics or an appropriate associated field. Doctorate / PhD candidates would be given higher preference.
• At least 3 years lecturing / facilitation experience for industry.

• Research track record (publications in Data Science, Artificial Intelligence, Machine Learning).
• Lecturing experience at a University of Technology or similar.
• Own PC / Laptop with a high quality microphone and webcam for virtual lectures.
• Strong and stable internet connection for online facilitation.
• Experience in designing data science courses and adapting them to industry needs will be advantageous.
• Industry experience in data science, data visualisation and preparation will be advantageous.
• Advanced Knowledge of Artificial Intelligence.
• Advanced Knowledge of Machine Learning.
• Experience using RapidMiner, Google CoLab or Jupyter Notebooks.

• Teach and facilitate Foundation of Data Science Short Courses targeted at industry.
• Develop and curate course content.
• Assist student queries and provide guidance on practical application of data science, data visualisation and data preparation.
• Practical demonstrations using RapidMiner or related software.
• Demonstrate a high degree of competency in digital communication tools, including Microsoft Teams, Google Classrooms, Zoom and Learning Management Systems (LMS).
• Provide mentorship and consultation for students where necessary.

Contact Person: Ms Nelisiwe Msimango

Email:

Status of Position: Part time contract (6 months)

• A fully completed specified application form.
• A detailed curriculum vitae (CV) explicitly stating experience or knowledge in the above mentioned fields.
• A Covering letter.
• Certified copies of all academic records and certificates.
• Current contact information of referees.
• Closing date: 01 June 2026 at 16:00.

While DUT strives for equal opportunities, preference will be in terms of the University's equity policy.

The University reserves the right not to appoint.