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PhD Scholarship in Machine Learning Methods for the Analysis of Time Series of Spatial Data from GNSS Sensor Networks

Durham University - Department of Computer Science

Qualification Type: PhD
Location: Durham
Funding for: UK Students, EU Students
Funding amount: £15,009 based on 2019/2020 stipend
Hours: Full Time
Placed On: 5th June 2019
Closes: 15th July 2019

Funding for: UK students and EU students

Funding amount: £15,009 based on 2019/2020 stipend

The Department of Computer Science at Durham University is pleased to offer a fully funded PhD studentship for a collaborative project with industry, jointly sponsored by European Regional Development Funding, Durham University and Geospatial Research Ltd.

This studentship will start from October 2019 and the successful applicant will receive a scholarship for three years (subject to satisfactory progression). The studentship includes:

  • Domestic fees supported by the industry partner. Please note non-EU international students will need to pay the balance of their fees.
  • A stipend equivalent to the Research Councils UK National Minimum Doctoral Stipend (£15,009 as of 2019).

The successful applicant will be based in the Department of Computer Science of Durham University, and the Geospatial Research premises in Durham supporting the company research.

Project Description:

Geospatial Research Ltd deploys GNSS (Global Navigation Satellite System) sensor networks in geologically sensitive areas. The data collected have the form of time series of 3D vectors representing distances between pairs of sensors. In a typical processing pipeline, the data are smoothed and events are detected as discontinuities in the time series.

The aims of the project are:

  • increase understanding of the signal noise decomposition of the collected data;
  • test utilisation of machine learning techniques for early event detection and event prediction;
  • development of methods for the optimisation of the deployed network.

Entry Requirements:

For entry to the PhD you will be required to have achieved a 2:1 Bachelor's degree in an appropriate subject, from a recognised university (or equivalent). Strong programming ability in a high-level language and a highly competent mathematical background are essential. Prior experience in machine learning is beneficial although not essential.

International students would also need to provide evidence of English language competency, such as a minimum overall IELTS 6.5 score of which no element of less than 6.0 (or equivalent).

How to apply:

Applicants are encouraged to make informal enquiries to Dr Ioannis Ivrissimtzis or Dr Noura Al-Moubayed (,

If you meet the eligibility criteria, please make an application via the university applications page at:

(In your application, specify project title: Machine Learning for GNSS sensor networks, departmental contact: Ioannis Ivrissimtzis)

Decisions will be made on applicants as they are received. The Department holds an Athena Swan Bronze award, highlighting its commitment to promoting women in Science, Engineering and Technology.

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