PhD position in New Zealand: Rock glacier change analysis using machine learning
shelley....@gmail.com
Dear all,
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
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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:
- Application form (available here)
- Cover letter explaining motivation for doing a PhD outlining interest and experience in geospatial methods and analysis (maximum two pages)
- Curriculum Vitae including a list of any prior publications.
- Contact details of at least two academic or professional referees.
- A GPA report obtained from https://support.scholaro.com/portal/kb/articles/canterbury (those with New Zealand or United States qualifications are not required to use Scholaro).