PhD Studentship: Fibre Optics and Machine Learning for Volcano Monitoring and Research

4 weeks ago

Norwich, Norfolk, United Kingdom jobs.ac - Jobboard Full time

Project Overview

This PhD studentship is an exciting opportunity to contribute to the development of new methodologies in photonic sensing and machine learning for volcano monitoring. The project aims to utilize emerging machine learning methods to process distributed sensing data from Mount Ruapehu Volcano in New Zealand, addressing key questions such as:

  • How can distributed sensing improve detection of small signals of unrest?
  • What is the improvement of subsurface imaging using distributed sensing over traditional sensors?
  • What additional understanding of volcanic processes can be gained from using distributed sensing?
  • How can distributed sensing be integrated into regular monitoring operations?

The student will use and adapt existing distributed sensing processing algorithms for a volcanic setting, test them on existing data, and deploy equipment for new data acquisition. Results will be analyzed in context with other observations.

Training and Support

Training will be provided in distributed sensing, geoscientific methods, machine learning techniques, and volcanic processes. The student will spend time in New Zealand, learning about the field site and other observation data.

Person Specification

Applicants must hold, or expect to receive, a degree in a relevant geoscience, computing, or physical sciences discipline. Numerical literacy and experience with Unix-based operating systems and/or Python are desirable but not essential.

Funding Details

The studentship is subject to confirmation of funding under the BBSRC-NERC DLA award scheme. Successful candidates will be awarded a fully-funded studentship, including fees, maintenance stipend, and research costs. A limited number of studentships are available to international applicants.

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