Jobs:Job-01225

From CSDMS
PhD position in New Zealand: Rock glacier change analysis using machine learning
University of Canterbury, , New Zealand
Apply before: 30 June 2023


We are looking for a PhD student in to join our team at the Waterways Centre, University of Canterbury, New Zealand.


The successful candidate for this PhD position (three years, full-time position) may be funded either by a GRI scholarship (details below) or a University of Canterbury scholarship, and will work on a project entitled “Towards a machine learning driven framework for quantifying regional scale rock glacier change in mountain regions”. The successful candidate will work on further developing a robust and transferable workflow that is capable of mapping rock glaciers from globally applicable satellite data. The successful candidate will work with colleagues in the School of Earth and Environment at the University of Canterbury, as well as with Associate Professor Ben Robson at the University of Bergen, Norway. Research stay(s) in Norway is(are) possible to facilitate collaboration. See below for detailed project description.

Please don’t hesitate to contact me for further information, and please forward this advert to suitable candidates who may be interested.

Kind regards,
Shelley MacDonell



Project description:
Towards a machine learning driven framework for quantifying regional scale rock glacier change in mountain regions

Main supervisor: Shelley MacDonell (School of Earth and Environment)

Project description: Snow, ice and permafrost are in a state of rapid change, directly impacting water resources, natural hazard occurrence and habitat availability in mountainous regions. While glacial and nival variability has been relatively well constrained using Earth Observation (EO) data, large uncertainties still remain in the state of mountain permafrost, including features such as rock glaciers. Recent advances in machine learning and computer vision offer new opportunities to automate detection and monitoring of rock glaciers over larger scales. The aim of this PhD thesis will be to develop a machine learning framework to reliably map rock glaciers in different environments at regional scales using EO datasets from Aotearoa New Zealand, the Andes, and Norway. The framework can work towards looking at changes over time. The successful candidate will be encouraged to explore geospatial portals such as Google Earth Engine or the Microsoft Planetary Computer as well to develop open-source scripts and routines.

The ideal candidate will have the following skills: Experience with programming, in particular machine learning libraries such as Tensorflow or Pytorch; Geospatial analysis including GIS and remote sensing is essential; Familiarity with methods such as differential radar interferometry (DInSAR), time series analysis, and topographic analysis are an advantage.

Geospatial Research Institute Toi Hangarau PhD Scholarship 2023

We are pleased to announce that we are now accepting applications for the 2023 Geospatial Research Institute (GRI) scholarship. The GRI scholarship has been implemented with the aim to increase the amount of novel geospatial research in all areas across the University of Canterbury.

Scholarship name: The Geospatial Research Institute PhD scholarship

Scholarship value: Total NZ$35000/year, plus fees and $2000 expenses.

Funding period: The scholarship is tenable for the period necessary to complete up to 360 points of enrolment

Number of scholarships: One

Closing date for applications: 30 June 2023, 17:00 pm NZ Time.

Prospective PhD student applications must include the following five items:


Of interest for:
  • Terrestrial Working Group
  • Artificial Intelligence & Machine Learning Initiative