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Saving Water with Smart Irrigation and Monitoring System based on Machine Learning

  • Full or part time
  • Application Deadline
    Friday, February 22, 2019
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

The overall aim of this project is to explore the capacity of deep machine learning techniques to analyse and extract meaningful features from meteorological data, soil moisture sensing data, and plant based sensory data (thermal imaging). The features will be fused and fed into a decision layer, in which the decisions, such as when irrigation is required and how much water are needed, will be automatically made.
In this PhD project you will face the challenge of developing innovative strategies to leverage the power of deep learning algorithms (arguably the fastest growing Artificial Intelligence paradigm) and extract agricultural knowledge in academic and industrial research environments.
The student will join an exciting research and training environment under the supervisions of computer scientists and agriculture specialists from both academia and industry. The student will be given special trainings, such as machine learning courses and irrigation training sessions. The studentship will include an internship period at Primafruit Ltd.

What is the CTP?
This funded project forms part of a BBSRC-funded Waitrose Collaborative Training Partnership (CTP) between the Waitrose Partnership, their international food production and supply companies, Lancaster University, the University of Reading, University of Warwick and Rothamsted Research. Between 2017 and 2023, the CTP will deliver studentships on the themes of sustainable crop production, sustainable soil and water and biodiversity and ecosystem services in agriculture. This project is based at Lancaster University.

Funding Notes

Applicants should hold a minimum of a UK Honours Degree at 2:1 level or equivalent in subjects such as Computer Science, Environmental Science, Engineering, Mathematics or Physics. It is desirable for applicants are to show experience in (a combination of) the following skills:
1. Machine learning background
2. Proficient programming skills
3. Knowledge of agricultural technology

Funding
Full studentships (UK/EU tuition fees and stipend (£14,777 2018/2019 tax-free) for 4 years for UK/EU students subject to eligibility criteria. Unfortunately, studentships are not available to non-UK/EU applicants.

References

For further details please contact Dr Jungong Han: [email protected] or for application queries contact Roz Wareing, [email protected] . Visit the Waitrose CTP Website www.sustainableagriculturewaitrose.org/training/ctp/

Follow the instructions on How to apply of the Waitrose CTP website http://sustainableagriculturewaitrose.org/training/ctp/ctp-application-process/how-to-apply/

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