We are seeking a motivated and collaborative individual to join our team as a Research Associate in Multi-Array Sensing System for Non-Ferrous Obscured Waste (MASSNOW). This role offers an exciting opportunity to contribute to the development of a real-time vision system (RGB+NIR) for recognising or differentiating common shapes in scrap metal, followed by integrating multimodal information (magnetic and vision) for optimal detection, within a dynamic and inclusive environment.
You will be responsible for:
We welcome candidates who bring diverse perspectives, experiences, and approaches to their work.
About You
We encourage applications from individuals with a wide range of backgrounds and experiences. You should demonstrate:
Essential Criteria:
Desirable Criteria:
We value transferable skills and real-world experience as much as formal qualifications.
Our benefits include:
For more information, please see University of Manchester Benefits. You can also find information on our Flexible and Hybrid working here.
We are an open place of enquiry and challenge. We embrace and celebrate difference, diversity and debate, and we pride ourselves on being a place of education, learning and community where we are able, within the law, to question and test received wisdom, express new ideas and explore controversial or unpopular topics and opinions. Find out more from our Freedom of Speech Policy.
Enquiries about the role, shortlisting and interviews
Name: Michael O’Toole
Email Address: michael.otoole@manchester.ac.uk
Name: Prof. Hujun Yin
Email Address: hujun.yin@manchester.ac.uk
General enquiries and administrative support
recruitmentservices.people@manchester.ac.uk
Technical and job portal support: jobseekersupport.jobtrain.co.uk/support/home
This role is not eligible for Skilled Worker visa sponsorship. Applicants must demonstrate the right to work in the UK.
Applications close at midnight on the closing date.
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