2020 applicants
Postgraduate Research Opporunities

AI-farming: AI-powered intelligent autonomous systems for smart farming

Details

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)

This opportunity is now closed. View our open opportunities.

Overview

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:

  • novel sensing technology to acquire crop data with unprecedented resolutions for timely non-destructive monitoring;
  • flexible UAV platform for field-scales applications;
  • IoT to access various ground data;
  • Artificial Intelligence algorithms to analyse an unprecedented volume/velocity/variety of data with an unexampled speed and depth.

The project

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.

Funding

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.

Supervisors

Professor Tracy Lawson

Co-supervisor

School 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.

Professor Klaus McDonald-Maier

Co-supervisor

School 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.

Criteria

Essential

  • BSc (first class)/MSc/MPhil in Computer Science, Electronics Engineering, Mathematics, Automation or a related subject. 
  • Strong theoretical and applied knowledge in machine learning, as well as good programming skills in Matlab/Python/C++ or other languages of choice.
  • The successful candidate would be expected to meet our English language requirements.

Desirable

  • Ability and experience to operate small Unmanned Aerial Vehicles (UAVs).
  • Experience of working on robotics project(s) by using Robot Operation System (ROS).
  • Experience of working on precision agriculture project to a successful completion.
  • Experience of high-quality publication(s) in English.

How to apply

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.

Instruction to applicants

When you apply online you will be prompted to fill out several boxes in the form:

  • For "Course title" please put "Computer Science", tick "postgraduate research" and hit "search". This will bring up a list of matching courses, select the one marked "full time" and "PhD".
  • For "Proposed research topic or area of research" please put the title of this studentship (SCH33: AI-farming: AI-powered intelligent autonomous systems for smart farming )
  • For "If you have contacted a potential supervisor..." please put the name of the lead supervisor (Dr Jinya Su).

If you have any informal queries about this opportunity please email the lead supervisor, Dr Jinya Su (j.su@essex.ac.uk).

You can find the terms and conditions of this studentship here (PDF).

Student and academic working at a board together
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