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Research Associate in image processing with machine learning
Sackville Street, Manchester

Job reference: SAE-017029

Location: Sackville Street, Manchester

Closing date (DD/MM/YYYY): 27/07/2021

Salary: £32,816 to £40,322 per annum depending on relevant experience

Employment type: Fixed Term

Faculty/Organisation: Science and Engineering

Division: Department of Electrical & Electron Eng

Hours per week: Full time

Contract Duration: Fixed term from 1 October 2021 until 31 July 2022

School / Directorate: School of Engineering

An important application of Smart Agriculture is crop monitoring. Fruit bearing trees need close monitoring to detect early issues affecting the quality and quantity of their yield. In this project, the focus is on olive trees in Jordan. We aim at building low-cost prototypes of devices to perform the challenging task of pre-harvest monitoring of the olive crops/trees. For this task, our Jordanian partners Jordan University of Science and Technology will use drones to collect high resolution images of the olive trees in different olive orchards in Jordan, at different growth stages in order to estimate their healthiness and their readiness for harvesting. A Computer Vision (CV) system will be developed using state-of-the-art Machine Learning (ML) and Deep Learning (DL) models to process the collected images and produce real-time decisions/recommendations.

The purpose of this job is to build a ML/DL-based CV model for the classification of images of olive crops/trees into many classes related to the health of both the crops and trees and the ripeness of the crops and its readiness for harvesting.

You should hold a PhD or equivalent in Computer Science or related field using machine learning algorithms.

The Department of Electrical & Electronic Engineering is committed to promoting equality and diversity, including the Athena SWAN charter for promoting women’s careers in STEMM subjects (science, technology, engineering, mathematics and medicine) in higher education. We particularly welcome applications from women for this post. Appointment will always be made on merit. For further information, please visit

Blended working arrangements may be considered       

Please note that we are unable to respond to enquiries, accept CVs or applications from Recruitment Agencies.

Enquiries about the vacancy, shortlisting and interviews:

Name: Fumie Costen.


General enquiries:


Technical support:

This vacancy will close for applications at midnight on the closing date.

Please see the link below for the Further Particulars document which contains the person specification criteria.


The closing date for this job has now passed.