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PhD Studentship: Application of machine learning to screen hyperspectral data for important soil and plant properties.

University of the West of England, Bristol - Faculty of Health and Applied Sciences

Qualification Type: PhD
Location: Bristol
Funding for: UK Students, EU Students, International Students
Funding amount: From £16,602 tax-exempt stipend, currently award, per annum.
Hours: Full Time
Placed On: 4th August 2022
Closes: 28th August 2022
Reference: 2223-JAN-HAS15

Application of machine learning to screen hyperspectral data for important soil and plant properties.

An opportunity to apply for a funded full-time PhD with UWE Bristol and Hartpury University.  The studentship will be funded by the Faculty of Health and Applied Sciences: Ref 2223-JAN-HAS15.

The expected start date of this studentship is January 2023

The closing date for applications is 28th of August 2022. 

About the Studentship

The aim of this project is to apply hyperspectral technology to the measurement of soil and plant properties. Hyperspectral technologies, along with computer vision and machine learning techniques, allows for new and exciting studies and practical applications in agriculture (soils and plants). The monitoring of biophysical properties associated with land used for farming is of great importance to our understanding of sustainable production methods. This project is a collaboration between Hartpury University and UWE to develop applied field monitoring solutions to improve land management decisions. This project will collect soil and plant spectral data from field and laboratory studies and use the latest computer vision and machine learning techniques to quantify important measures e.g. nutrient content, plant biotic and abiotic stresses. As land management becomes increasingly data informed, including temporal and spatial changes in soil and plant properties, more timely and efficient use of information is needed to support farming practices. The project would suit a student with a background in computer science and interest in environmental studies. The objectives of the work are to:

  1. Review existing spectral technology, and its application for soil and plant monitoring 
  2. Carry out studies to collect spectral data to train and validate prediction models
  3. Propose a technological solution that enhances field monitoring

For an informal discussion about the studentship please contact Dr Andy Wetten, Dr Joel Allainguillaume, Dr Wenhao Zhang or Professor Matt Bell.

Funding details

The studentship is available from 1 January 2023 for a period of three years, subject to satisfactory progress and includes a tax-exempt stipend, which is currently £16,602 per annum.

In addition, full-time tuition fees will be covered for up to three years for Home and Overseas applicants.

Eligibility criteria

Applicants must have a First-Class or Upper Second-Class BSc in an appropriately related subject area (for example, computer science, biology, environmental science) with a grounding in laboratory-based research. Although not essential, a Master’s degree in a related discipline, and/or postgraduate experience is desirable. The candidate’s degree relevant to the studentship should demonstrate their potential for practice-led research.

A recognised English language qualification is required. Applicants whose first language is not English require a recognised English language qualification. The minimum entry requirement is GCSE English at grade C or above or IELTS score 7.0 or TOEFL score 600 (or demonstrable equivalent).

How to apply

Please submit your application online. When prompted use the reference number 2223-JAN-HAS15.

Supporting documentation: you will need to upload as attachments to your application the following documents:

  • A curriculum vitae
  • Copies of academic transcripts
  • A covering letter outlining your suitability for the studentship
  • A recent piece of critical writing you have completed (max 3000 words)
  • If English is not your first language, certification of English language qualification

References: you will need to provide details of two referees as part of your application.

Closing date for applications: 28th of August 2022.

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