Expires on: 08/13/2024
Description
Explore the cutting-edge field of Quantum Technology Engineering with the University of Southampton’s PhD Studentship in Efficient End-to-End Quantum Machine Learning Strategies for Imaging. This opportunity, led by Prof Thomas Blumensath, offers substantial training in scientific, technical, and commercial skills alongside a research project focused on advancing quantum machine learning applications.
This project delves into efficient quantum machine learning strategies, exploring the interaction of classical dimensionality reduction methods with quantum encoding and efficient quantum machine learning. The focus is on computational imaging, specifically in tomographic imaging, addressing challenges in large, three-dimensional data sets. The research aims to develop more efficient methods for tasks such as image classification, anomaly detection, and image de-noising.
Eligibility:
- A very good undergraduate degree (at least a UK 2:1 honours degree or its international equivalent).
Documents:
- Curriculum Vitae
- Two reference letters
- Degree Transcripts/Certificates to date
How to Apply:
Apply online by searching for a Postgraduate Programme of Study on the University of Southampton website. Select program type as Research, Faculty of Engineering and Physical Sciences, and then choose “PhD iMR.” In Section 2 of the application form, insert the name of the supervisor (Prof Thomas Blumensath).
Applications should be sent to: feps-pgr-apply@soton.ac.uk.