Senior Lecturer/Lecturer/Junior LecturerExpired

Department Description/Departement Beskrywing

Faculty of Economic and Management Science (EMS)

Department of Statistics and Actuarial Science

Senior Lecturer/Lecturer/Junior Lecturer: Department of Statistics and Actuarial Science (Two posts)

(Stellenbosch Campus)

Ref. EBW08/162/0626

The Department of Statistics and Actuarial Science at Stellenbosch University (SU) offers both undergraduate and postgraduate training in statistics/mathematical statistics, data science, actuarial science and financial risk management. Members of the Department are also actively engaged in research and consulting in these fields. There are currently vacant positions in the Department at junior lecturer, lecturer and senior lecturer level.

The Department's current need is for teaching and research in mathematical statistics, which underpins both theoretical advances in statistics and the foundations of modern data science and statistical learning. Our mathematical statistics stream equips students with a deep understanding of probability, inference, and the principles governing statistical and machine learning methods. This expertise is essential for training graduates who can critically assess, develop, and extend modern analytical tools. The incumbents will contribute to this mission through the teaching of mathematically grounded modules in both mathematical statistics and the theoretical aspects of data science.

For the purposes of this advertisement the following definitions will apply:

• "Mathematical statistics": the study and teaching of statistical methods from a rigorous mathematical perspective, with emphasis on probability theory, statistical inference, asymptotic theory, and the theoretical foundations of statistical and machine learning methods. It involves the development, analysis, and justification of statistical procedures using advanced mathematical tools beyond application alone.
• "Data science": data science techniques with a strong emphasis on mathematical statistics, including statistical learning theory, and the mathematical foundations of machine learning.

Further information is available on the Department' s website at Department of Statistics & Actuarial Science

Duties/Pligte

• Teaching and developing undergraduate and postgraduate module content in mathematical statistics and/or data science.
• Participating in the Department's teaching, academic support activities and research activities.

Assisting With

• Junior Lecturer/Lecturer/Senior Lecturer: Administrative and tutorial support related to undergraduate modules, honours project supervision;
• Lecturer/Senior Lecturer: Honours project and master's supervision; and
• Senior Lecturer: Honours project, master's and PhD supervision.

Job Requirements/Pos Vereistes

• Education:

• Junior Lecturer/Lecturer/Senior Lecturer: A completed bachelor's degree with a specialisation in mathematical statistics and/or data science, as well as a NQF 8 qualification (honours equivalent) in mathematical statistics and/or data science.
• Junior Lecturer: Currently enrolled for, or having completed all coursework requirements towards, a course-work master's degree (where coursework comprises at least 33% of the degree credits) in mathematical statistics and/or data science.
• Lecturer/Senior Lecturer: A completed course-work master's degree (where coursework comprises at least 33% of the degree credits) in mathematical statistics and/or data science.
• Senior Lecturer: A completed PhD in mathematical statistics and/or data science.
• Evidence of substantial undergraduate-level training in pure mathematics, to at least second-year level (and preferably further), covering topics such as linear algebra,

real analysis and/or advanced calculus.

• Evidence of substantial undergraduate-level training in postgraduate mathematical statistics topics such as:

• Probability theory (measure-theoretic or advanced calculus-based);

• Statistical inference (estimation theory, hypothesis testing);

• Asymptotic theory; and

• Linear models and/or multivariate analysis.

• Teaching ability and module development:

• Junior Lecturer: The ability to teach or tutor mathematical statistics and/or data science. The ability to develop undergraduate and postgraduate modules in mathematical statistics and/or data science.

• Lecturer: The ability to teach mathematical statistics and/or data science, especially to large undergraduate classes. The ability to develop undergraduate and postgraduate modules in mathematical statistics and/or data science.

• Senior Lecturer: Proven experience in teaching mathematical statistics and/or data science at undergraduate and postgraduate level, especially to large undergraduate classes. Proven experience in developing undergraduate and postgraduate modules in mathematical statistics and/or data science.

• Research supervision:

• Lecturer: The ability to supervise honours and master's students in mathematical statistics and/or data science.

• Senior Lecturer: The ability to supervise honours, master's (with proven experience) and PhD students in mathematical statistics and/or data science.

• Lecturer: Currently registered for or intending to register for a PhD in mathematical statistics or data science.

• Research:

• Senior Lecturer: Research output with respect to mathematical statistics and/or data science in accredited scientific journals and the ability to independently build a research profile.
• Experience in recognised modern statistical programming languages, for example: R, MATLAB, Python (NumPy, SciPy).

Recommendation/Aanbeveling

• Exposure to measure-theoretic probability and/or stochastic processes.

• Junior Lecturer:
• Intention to complete a master's degree (shortly after appointment) in mathematical statistics and/or data science, with the intention of progressing to PhD studies.
• Lecturer:
• PhD in mathematical statistics or data science.
• Proven experience in research supervision of honours and master's students.
• Research output with respect to mathematical statistics and/or data science in accredited scientific journal(s).
• Senior Lecturer:
• Proven experience in the supervision of PhD students.

How To Apply/Hoe Om Aansoek Te Doen

#PAS

Applications

Prospective applicants should include the following documentation in their application submission:

• A full curriculum vitae (CV).
• Certified copies of highest degree obtained and mark transcripts of marks achieved in all undergraduate and postgraduate modules.
• A copy of your project/thesis for your highest degree obtained as well as a short (maximum one page) summary of:

• The aims and objectives of the project/thesis;
• Any past/future research; and/or
• Teaching experience in the relevant field(s).

• Name(s) of supervisors (for highest degree obtained) with contact details.
• A cover letter (maximum one page) in which you briefly demonstrate your suitability for the position you are applying for, including your background in mathematical statistics and/or data science, evidence of mathematical training, supervision history and your ability to teach statistical methods at a high theoretical level. Applicants should clearly describe courses taken in mathematics and statistical theory in their mark's transcripts.

Shortlisted candidates will be required to participate in a mock lecture on a specified mathematical statistics topic.

The University is committed to employment equity (EE), and appointments will be made in line with the institutional EE Plan.

Stellenbosch University reserves the right not to make an appointment.

Your application, comprising a comprehensive curriculum vitae (including the names and email addresses of at least three references), must reach the University