Ad Hoc Scholarships
Masters / PhD Opportunities in Statistics and Digital Soil Mapping (2026-2027)
Main supervisor: Dr Stephan van der Westhuizen; Statistics lecturer at Dept of Statistics and Actuarial Science
and member of MuViSU at Stellenbosch 肆客足球.
We are currently looking for master’s / PhD students to be part of an exciting multidisciplinary research
project in statistical modelling, data visualisation, and digital soil mapping (DSM). This research project forms
part of a collaboration with the Dept of Soil Science (SU), and the Centre for Multi-dimensional Data
Visualisation (MuViSU - https://www.sun.ac.za/english/faculty/economy/MuViSU).
DSM is a rapidly growing research field both locally and internationally and refers to the creation of soil maps
by using statistical models, such as machine learning models. DSM creates these soil maps across large areas
and is an important tool for monitoring soil properties. However, many data sets in soil science present
complex challenges - such as spatial dependence, measurement error, and heterogeneity - that must be
addressed within the statistical models. If these complexities are ignored, then the resulting soil maps could
be suboptimal. We are therefore looking for postgraduate students in statistics to be part of this project and
to make meaningful impacts on statistical methodology / machine learning as well as in important
environmental issues in South Africa.
The primary research aim of this project is to improve the accuracy of digital soil maps by using machine
learning and by accounting for various data complexities. The selected students will get exposure in R/Julia
statistical computing, digital soil mapping and machine learning. Refer to the following link to a short video
which gives a brief overview of the project: https://youtu.be/IJtC3wSYwFg.
Student background: Appropriate degrees to apply for master’s/PhD (refer to the faculty’s website:
https://www.sun.ac.za/english/pgstudies/Pages/EMS/Faculty-of-Economic-and-Management-
Sciences.aspx). The selected students should have an interest in working with spatial data, machine
learning/predictive modelling and geographic mapping. Students with experience and/or interest in machine
learning/predictive modelling are particularly encouraged to apply.
Standard NRF bursaries are potentially available for the selected students, beginning early 2026. To apply,
send your CV, academic transcripts, a brief motivation letter, and the contact details of two references to Dr
Stephan van der Westhuizen (stephanvdw@sun.ac.za). Applications should be sent by 23 June 2025 (17:00).
If your application is successful, you will be provided with the supervisor’s NRF project ID so that you can
apply for a grant holder-linked project on the NRF application portal (https://nrfconnect.nrf.ac.za/).
Successful applicants will also get assistance from the supervisor to apply for these projects on the NRF
portal. The applications to the NRF closes on 4 July 2025.
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