Research Assistant in Vision System

The University of Manchester

Location:ManchesterSalary:£32,080 to £36,636 per annum, depending on relevant experienceHours:Full TimeContract Type:Fixed-Term/ContractPlaced On:9th September 2025Closes:23rd September 2025Job Ref:SAE-029582

Job reference: SAE-029582

Salary: £32,080 to £36,636 per annum, depending on relevant experience

Faculty/Organisational Unit: Science and Engineering

Location: Manchester

Employment type: Fixed Term

Division/Team: Department of Electrical and Electronic Engineering

Hours Per Week: 35 hours per week

Closing date (DD/MM/YYYY): 23/09/2025

Contract Duration: 12 months (from 1st October 2025 to 31st September 2026)

School/Directorate: School of Engineering

The overall aim of this project is to develop a real-time monocular vision system for measuring bio test-tube heights in a rack and alignments in the space-defined labware carriage. The vision system, including a suitable camera and an embedded system, will enable real-time acquisition of images of the tube carriage, from the side of the carriage, and subsequent image processing algorithms to extract and measure the heights of the tubes of misaligned tubes. The development will enable full automation in Azenta’s and similar biological sample storages or banks and making an impact of UoM research to industrial applications. Objectives are:

1. Constructing a suitable monocular vision system in a confined space (labware carriage).
2. Developing real-time embedded system and associated image acquisition and photogrammetry algorithms for accurately measuring labware alignments and heights in the carriage.
3. Integrating the developed vision system into labware automation system to enable individual labware identification and management.

As an equal opportunities employer we welcome applicants from all sections of the community regardless of age, sex, gender (or gender identity), ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit.

Our University is positive about flexible working – you can find out more here.

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: Prof. Hujun Yin

Email: hujun.yin@manchester.ac.uk

General enquiries:

Email: People.Recruitment@manchester.ac.uk

Technical support:

Jobtrain: 0161 850 2004 jobseekersupport.jobtrain.co.uk/support/home