This project aims to leverage advances in ultrasonic testing, including optical fibre-based distributed acoustic sensing and physics-enhanced machine learning, to improve the reliability of nuclear waste storage monitoring.
The security of energy generation and management facilities is vital to national defense. These assets often operate under extreme environmental conditions, such as high pressure, high temperature, or ionizing radiation. Nuclear waste storage is a key example where long-term container integrity monitoring is crucial but challenging due to hazardous conditions and the scale of structures involved.
The project seeks to utilize recent developments in ultrasonic testing, optical fibre-based distributed acoustic sensing, and machine learning to develop reliable long-range monitoring solutions. It involves assessing the practical limitations of these sensing modalities and developing techniques to overcome them using modern computing. Both active (inducing acoustic signals) and passive (monitoring leak noise, ambient vibrations, seismic activity, etc.) methods are considered, along with an optimal framework for utilizing available capabilities. The student will engage in numerical and analytical modeling, develop machine learning frameworks for metamodelling and decision support, and conduct experimental tests on mock-up configurations.
For informal inquiries, please contact Dr. Michal Kalkowski at M.Kalkowski@soton.ac.uk.
Funding for this project is provided by the Centre for Doctoral Training in Complex Integrated Systems for Defence & Security (CISDnS). The program recruits motivated candidates across themes of Digital, Physical, and Biological systems to foster a diverse and interconnected training environment. More information about the Centre and its training program can be found at https://cisdns-cdt.ac.uk/.
For discussions related to the CISDnS CDT, please contact the directorate at cisdns@soton.ac.uk.
This PhD studentship is open only to UK applicants. The project is suitable for applicants with backgrounds in mechanical engineering, acoustics, numerical modeling, scientific computing, signal processing, machine learning, or applied mathematics.
CISDnS is committed to promoting equality, diversity, and inclusivity. We welcome applicants regardless of gender, ethnicity, disability, sexual orientation, or age, and consider flexible working arrangements and career breaks. The university offers generous maternity policies, onsite childcare, and other benefits supporting work-life balance.
Entry requirements: A very good undergraduate degree (minimum UK 2:1 honours or equivalent). We accept various forms of prior learning to meet diversity objectives.
Funding: Full-time studentships cover UK tuition fees and provide an enhanced tax-free stipend of approximately £24,700 per year for four years, including a research, travel, and activities budget.
How to apply:
Search for a Postgraduate Programme of Study (soton.ac.uk). Select Full-time or Part-time, Research, 2025/26, Faculty of Engineering and Physical Sciences, then choose “iPhD Complex Integrated Systems in Defence & Security (Full-Time).” In Section 2 of the application, specify Dr. Michal Kalkowski as the supervisor.
Application materials should include:
* A curriculum vitae detailing your academic record and research interests.
* Names and institutional email addresses of two academic referees, who will be contacted automatically upon submission.
* Your academic transcript and degree certificates (translated if not in English). Both BSc and MSc transcripts are required if applicable.
* A brief statement of your research interests in the Personal Statement section of the application form.
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