Digital Twin technology is a digital model of a physical system (such as a robot or an aircraft engine), which can manufacturers and engineers to better understand and predict physical product performance, and provide continuous monitoring and predictive maintenance insights to improve product efficiency and reliability. Smart Robots (including collaborative robots and professional robots) are widely used across various industries, such as aerospace, automotive, energy, healthcare, and manufacturing for several applications. These robots can learn from their experience and environment and build their capabilities based on their knowledge. Collecting data on real robots might be time-consuming, potentially dangerous, and expensive. A Digital Twin technology is designed to help operators create models to virtually program and optimize robotic systems and improve their interaction with humans.
The candidate will be based in the School of Engineering and Digital Arts and will work under the supervision of Dr Mahmood Shafiee, Reader in Mechanical Engineering, alongside several funded research projects. There is also an industry placement opportunity for the student to take up to six months, during which the student will work closely with a number of robotic companies and AI businesses across the UK.
Funding is available at the current home fee rate of £4,407.00 together with a maintenance grant of £15,285.00. Overseas candidates with First Class Degree or Master’s with Distinction classification will be offered an additional honorarium of £5,000 per annum towards their fees.
The application deadline is Monday 30 November 2020. Enquiries relating to the project should be directed to Dr Mahmood Shafiee firstname.lastname@example.org
Further details about the project, including the application link, can be found here: