[visionlist] PhD position: Saving Water with Smart Irrigation and Monitoring System based on Machine Learning

jungong han jungonghan77 at gmail.com
Mon Jan 28 07:10:10 -05 2019


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

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:
jungong.han at lancaster.ac.uk or for application queries contact Roz Wareing,
r.wareing at lancaster.ac.uk. 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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