PhD Research Studentships
Physically Interpretable Machine Learning (PIML) for digital analysis and design of complex dynamic systems
| Supervisors: | Yunpeng ZHU and Han ZHANG |
| Apply by: | 31 January 2024 |
| Start in: | September (Semester 1) |
Description
We aim to unlock the future of engineering excellence. Engineering systems such as building structures, vehicles, metamaterials, etc., are often subject to dynamic loads in their practical applications. Analysing and designing these complex dynamic systems for i.e., vibration isolation and sound absorption is particularly challenging due to their multi-dimensional nature and inherent nonlinearities. Data-driven and machine-learning methods have been widely applied to predict the dynamic behaviours of complex systems, but existing machine-learning models often operate as black-box solutions. This lack of transparency makes it difficult to produce interpretable and reliable decisions and designs for engineering applications.
The project aims to develop an innovative Physically Interpretable Machine Learning (PIML) framework to facilitate digital transformation in the analysis and design of complex spatial-temporal dynamic systems. We will develop innovative data/system science theories and methods based on sparse regression, nonlinear frequency analysis, and all relevant approaches. We will also conduct experimental studies in collaboration with academic and industrial partners to apply the developed approaches in practice. In this project, you will have the opportunity to collaborate with researchers from the UK, the USA, Netherlands, China, etc. High-quality international journal papers would be published to disseminate the research achievements.
Funding
Funded by: China Scholarship CouncilCandidate will need to secure a CSC scholarship.
Under the scheme, Queen Mary will provide scholarships to cover all tuition fees, whilst the CSC will provide living expenses and one return flight ticket to successful applicants.
Eligibility
- The minimum requirement for this studentship opportunity is a good honours degree (minimum 2(i) honours or equivalent) or MSc/MRes in a relevant discipline.
- If English is not your first language, you will require a valid English certificate equivalent to IELTS 6.5+ overall with a minimum score of minimum score of 6.0 in each of Writing, Listening, Reading and Speaking).
- Candidates are expected to start in September (Semester 1).
Contact
For informal enquiries about this opportunity, please contact Yunpeng ZHU or Han ZHANG.
Apply
Start an application for this studentship and for entry onto the PhD Mechanical Engineering full-time programme (Semester 1 / September start):
Please be sure to quote the reference "SEMS-PHD-535" to associate your application with this studentship opportunity.
| Related website: | https://www.sems.qmul.ac.uk/staff/y.zhu | |
| SEMS Research Centre: | ||
| Keywords: | Artificial Intelligence, Data Science, Machine Learning, Dynamics, Manufacturing, Mechanical Engineering, Systems Engineering, Data Analysis, Engineering Mathematics, Mathematical Modelling |