PhD Opportunities at University of Canterbury (NZ) – Please Share

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From: Alberto Ardid <alberto.ardid@xxxxxxxxxxxxxxxx>


We invite applications for 2 fully-funded PhD positions at the University
of Canterbury (Christchurch, New Zealand).
Hereâ??s a brief summary of each position:

   1. *PhD in Machine Learning for Volcano Eruption Forecasting*
   This project focuses on developing advanced machine learning
   methodologies for forecasting hydrothermal and volcanic eruptions. It
   leverages multi-sensor data (e.g., seismicity, deformation, gas emissions,
   and thermal anomalies) and includes both site-specific and generalized
   model development. The successful candidate will work with datasets from
   geysers and volcanoes worldwide. The position will be co-supervised by
   Dr. Alberto Ardid and Dr. David Dempsey at the University of Canterbury.
   Please direct initial inquiries to Dr. Alberto Ardid (
   alberto.ardid@xxxxxxxxxxxxxxxx). Application can be completed here
   <https://docs.google.com/forms/d/e/1FAIpQLSdJcdu4zZBp0uWETVNOFXXEy_a8R1k2ygI-HVEuvuht5D54HA/viewform>
   .
   2. *PhD in Physics-Based Modelling of Hydrothermal Eruptions*
   This position centers on using numerical models to understand the
   physical mechanisms behind hydrothermal eruptions in geothermal and
   volcanic systems. It involves simulating heat and fluid transport, phase
   change, and seal failure, with application to real eruption case studies.
   The project is part of a broader research effort into hydrothermal hazard
   assessment. The PhD will be co-supervised by Dr. David Dempsey and Dr.
   Alberto Ardid. For further information, please contact Dr. David Dempsey (
   david.dempsey@xxxxxxxxxxxxxxxx). To apply, visit this LINK
   <https://docs.google.com/forms/d/e/1FAIpQLSctNtLVlp1Zx722fD0f9xUeBWGZRl49P_4pxEgGI_RWObhypw/viewform>,
   where you will need to upload a CV and cover letter.

Both positions are fully funded, including a NZD $35,000/year stipend, full
tuition, and support for conference travel or research visits. Preferred
start is early 2026.

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