Title: SCH33: AI-farming: AI-powered intelligent autonomous systems for smart farming
Funding: A full Home/EU fee waiver or equivalent fee discount for overseas students (£5,103 in 2020-21) (further fee details - international students will need to pay the balance of their fees) plus a doctoral stipend equivalent to the RCUK Minimum Doctoral Stipend (£15,285 in 2020-21).
Application deadline: Tuesday 31 March 2020
Start date: October 2020
Duration: 3 years (full time)
Location: Colchester Campus
Based in: School of Computer Science and Electronic Engineering (in collaboration with School of Life Sciences)
From Defra’s statistics, UK Agriculture Sector (utilizing 71% country’s land, supporting 3.9M jobs) lags behind competitors in agricultural productivity.
Globally, agriculture is also facing severe challenges: 70% increase in food demand by 2050, decreasing natural resources and the requirement of reducing environmental footprint.
There is an urgent need to change from management strategies irrespective of stress severity and distribution to informative site-specific ones.
This studentship is a timely response and will embrace emerging opportunities:
This project, perfectly aligned with the themes of Environments and Intelligence, aims to undertake PhD research in AI-powered intelligent systems for smart farming.
The researched systems are expected to provide growers with crop stress diagnostics and intervention strategies. It will increase crop productivity while protecting the environment.
It is envisioned the highly interdisciplinary project, bringing together the expertise of Plant Physiology Lab and Embedded and Intelligent Systems Lab, will help place UK food production among the most productive, resilient and sustainable in the world.
The award consists of a full Home/EU fee waiver or equivalent fee discount for overseas students (further fee details), a doctoral stipend equivalent to the Research Councils UK National Minimum Doctoral Stipend (£15,285 in 2020-21), plus £2,500 training bursary via Proficio funding, which may be used to cover the cost of advanced skills training including conference attendance and travel.
Lead supervisorSchool of Computer Science and Electronic Engineering, University of Essex
Dr Jinya is a new lecturer in CSEE. His expertise is on intelligent autonomous systems by developing novel perception, decision and intervention algorithms to address the global challenges faced in agriculture and environment. He has delivered highly relevant projects (£3M) funded by EPSRC, BBSRC, Newton fund. In these topics, he published 24 flagship journal papers (3 ESI highly cited papers, 14 Q1, citation 770+, H-index 12), he established a stable national and international network to support the project.
Co-supervisorSchool of Life Sciences, University of Essex
Prof. Tracy Lawson is a Professor in School of Life Sciences and also the director of Essex Plant Innovation Centre (EPIC) and Plant Phenomics Research Facility. She has led a number of projects in the area of Agriculture and Environment, largely funded by BBSRC, NERC, Innovate UK. She has published 100+ journal papers in these areas and has extensive experience in supervising PhD students. She will provide support in plant stress monitoring and experimental design.
Co-supervisorSchool of Computer Science and Electronic Engineering, University of Essex
Prof. Klaus McDonald-Maier is a Professor in CSEE and the leader of Intelligent Embedded Systems Lab. He has extensive experiences in embedded system design and development, and AI applications for real-world problems. In these areas, he has published over 200 papers, successfully supervised a number of PhD students and received several millions’ research grants from EPSRC and Innovate UK. He will provide support on AI algorithm implementation and acceleration on embedded devices.
You can apply for this postgraduate research opportunity online.
Please include your CV, covering letter, personal statement, and transcripts of UG and Masters degrees in your application.
The University has moved to requiring only one reference for PhD applications and these can be received after a conditional offer has been made so the absence of these will not hold up the recruitment process.
When you apply online you will be prompted to fill out several boxes in the form:
If you have any informal queries about this opportunity please email the lead supervisor, Dr Jinya Su (email@example.com).
You can find the terms and conditions of this studentship here (PDF).