Fully Funded PhD Scholarship in HUMS: A fully funded PhD opportunity is available in the Faculty of Engineering and Physical Sciences for research into advanced Health and Usage Monitoring Systems (HUMS) using machine learning and digital twin technologies. This scholarship is open to both UK and international applicants and aims to revolutionize the monitoring, maintenance, and operational efficiency of machinery.
Fully Funded PhD Scholarship in Development of a New Generation Health and Usage Monitoring System (HUMS) using Machine Learning and Digital Twin Technologies
Designation:
Doctor of Philosophy (PhD)
Research Area:
Development of Health and Usage Monitoring Systems (HUMS) with a focus on machine learning, digital twin technologies, and their applications in mechanical systems.
Location:
Faculty of Engineering and Physical Sciences, University of Southampton, UK
Eligibility/Qualification:
- A UK 2:1 honours degree or its international equivalent, particularly in mechanical engineering or related fields (especially in materials, rotating machines, mechanical testing, and analysis).
- Experience with sensors and signal processing technologies.
- Proficiency in AI and machine learning methods, with applications in mechanical systems.
- Computing skills, especially in Matlab.
Job Description:
The selected PhD candidate will contribute to the development of a new generation of Health and Usage Monitoring Systems (HUMS) that integrate advanced machine learning models and digital twin technologies. The project has the potential to significantly enhance machinery performance, operation, and cost-efficiency by focusing on:
- Gearbox digital twin development.
- Generalized machine learning models for bearing and gear fault detection and diagnosis.
- Robust models for remaining useful life (RUL) prediction.
Applicants may choose to specialize in bearing/gear health monitoring, gearbox RUL modeling, or the development of gearbox digital twins. This role is ideal for individuals passionate about applying AI and ML techniques in mechanical systems.
How to Apply:
To apply, please follow these steps:
- Choose the programme type “Research” for the academic year 2024/25 within the Faculty of Engineering and Physical Sciences.
- Select “PhD Engineering & Environment (Full time)” on the next page.
- Include the name of the supervisor, Professor Ling Wang, in section 2 of the application form.
Applications should include:
- Your CV (résumé).
- Two reference letters.
- Degree transcripts/certificates to date.
For further queries, please contact the Faculty of Engineering and Physical Sciences at: feps-pgr-apply@soton.ac.uk.
Last Date to Apply:
30 September 2024
Don’t miss this opportunity to contribute to cutting-edge research and join a leading team working on advanced monitoring systems in mechanical engineering. Apply now to start your journey!
