AI and Robotics Engineer

This is a great opportunity to join an ongoing Knowledge Transfer Partnership (KTP) project that is developing an autonomous drone-based system for wind turbine blade inspection. The project is well into its development phase, and you will take over from the departing KTP Associate to complete the remaining development, integration, testing, and deployment of the system. You will play a key role in delivering the final stages of this project and the future strategy of Renewable Field Services Ltd, working with them at their base in Gateshead.

Working with the team at Renewable Field Services from their offices in Gateshead, you will be supported by an academic team from the School of Engineering, Physics and Mathematics at Northumbria University to complete the project aims and ensure knowledge transfer to the company.

The opportunities available to you:

• Completing and deploying a challenging and strategic R&D project that directly impacts the business
• Support and direction from an academic team with specialist knowledge and experience relevant to the project
• Potential to be retained in a permanent position within the company at the end of the project
• Potential for a performance-related bonus

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.

Find out more about Renewable Field Services Ltd: https://www.renewable-fs.com 

Find out more about School of Engineering, Physics and Mathematics at Northumbria University: https://www.northumbria.ac.uk/about-us/our-schools/school-of-engineering-physics-and-mathematics/ 

Find out more about Knowledge Transfer Partnerships: https://www.ktp-uk.org/ 

For informal enquiries please contact:

Dr Hamed Farokhi, Northumbria University: [email protected] 

Application submission:

To apply for this vacancy please click 'Apply Now', and submit:

1. A 2-page CV, highlighting how your skills and experience meet the project criteria (set out in the person specification document).

2. A one-page cover letter outlining relevant projects you have led or worked on.

3. A short video (max 3 minutes): this is your opportunity to tell us how your skills and experience are suitable for the role. To provide some context, this project is developing an autonomous drone-based wind turbine blade inspection system. The system uses a combination of LiDAR sensing and computer vision to determine the 3D orientation of a stopped wind turbine's blades, then generates and executes an autonomous flight path for the drone to inspect all blades. The drone communicates with a ground-station laptop via an onboard Raspberry Pi and a Wi-Fi link. The successful candidate will be expected to continue development, integrate and test the remaining modules, refine the user interface, and prepare the system for operational deployment. Upload the video to your preferred cloud provider (Google Drive, OneDrive, Dropbox, etc.) and include the link to the video clearly in your CV or cover letter (ensure the link allows access).
 

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