KTP Associate – Autonomous Control System (Smart Sweeping) (based in Dorking, Surrey RH4 1XF)
Dorking, Surrey RH4 1XF
£35,845 to £44,045 per annum
Entry level will be dependent on relevant skills and qualifications
Fixed Term - Up to 30 months
23.59 hours BST on Thursday 22 October 2020
This role will be involved in the development of an autonomous control system for Bucher Municipal street cleansing vehicles to improve road & public safety whilst optimising efficiency including;
- Supported by the Innovation & Simulation Manager & Systems Engineering Manager, this role involves development and the implementation of system, which can automate the sweeping functions of a truck mounted sweeper from the Bucher Municipal range of road sweeping machines. Specifically the aspect of AI / Deep learning around image processing and recognition to be able to automate vehicle functions to optimise the sweeping systems.
- This role has responsibility of software design for the automation of functions, liaising with the systems engineering team to develop communication over a company specific CAN Open implementation to a new schema of messages.
- The associate will need to ensure that any control software is fully tested and approved, meeting relevant standards using a defined release process, and that software release schedules are clearly defined internally and externally to Engineering.
- The role also involves collaborating with the Mechatronic Engineers to develop control software and system models of the machine.
- The associate would work along with the academic in developing simulation and AI systems.
Qualifications, skills and experience required:
- An undergraduate degree at 2.1 or above in Software Architecture/Engineering or similar, ideally with a Masters in a relevant similar discipline.
- Knowledge of engineering-electronics, computer engineering and a basic knowledge of microcontroller application. Be able to demonstrate an excellent knowledge of modelling systems using tools such as MATLAB & different toolboxes, e.g. deep learning, Simulink, etc.
- Be proficient in the use of editors such as Jupyter notebook, Google Co-lab, Spyder.
- Have a working knowledge of Linux
- Aware of the different types of frameworks for Computer vision and Deep learning, such as OpenCV, (YoLo), Tensorflow, Keras etc.
- Ability to demonstrate an understanding of CAN-based control systems and software, including sensors.
- A willingness to learn AI techniques, from the lengthy aspect of teaching, to the application and assessment of different approaches.
If you have any queries or questions or for an informal discussion please contact: Academic KTP Supervisor, Mr. Sam Wane: email@example.com
All applications should be completed and submitted using the Harper Adams e-Recruitment programme at http://jobs.harper-adams.ac.uk to be completed no later than midnight on 22nd October 2020.