Location: | Newcastle upon Tyne |
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Salary: | £33,000 to £40,000 dependent on experience |
Hours: | Full Time |
Contract Type: | Fixed-Term/Contract |
Placed On: | 17th April 2024 |
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Closes: | 20th May 2024 |
Job Ref: | 2366 |
ABOUT THE ROLE
This is a great opportunity to apply modern autonomous systems engineering and machine learning approaches to develop and deploy a system for autonomous inspection of wind turbines using unmanned aerial vehicles. You will be delivering this ambitious innovation project and become a key part of the future strategy of Renewable Field Services Ltd, working with them at their base in Gateshead.
You will lead a transformation project – a Knowledge Transfer Partnership (KTP) – to develop an autonomous technology for optimum and accurate inspection of wind turbines using unmanned aerial vehicles. Working at Renewable Field Services offices in Gateshead, you will work with an academic team from the Mechanical and Construction Engineering department at Northumbria University, who will provide support to meet the project aims.
The opportunities available to you:
For full details of qualifications, skills and experience required for the post, please review the Role Description document. Please also note the specific application document requirements below.
This is a fixed term role for a period of 30 months.
ABOUT THE TEAM
Find out more about Renewable Field Services Ltd: https://www.renewable-fs.com
Find out more about Mechanical and Construction Engineering at Northumbria University: https://www.northumbria.ac.uk/about-us/academic-departments/mechanical-and-construction-engineering/research/
If you would like an informal discussion about the role, please contact Dr Hamed Farokhi at hamed.farokhi@northumbria.ac.uk
ABOUT YOU
Further information about the requirements of the role is available in the person specification.
To apply for this vacancy please click 'Apply Now', and submit:
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