PhD studentship in the field of machine learning in medical imaging
Full tuition fees at the Home or Overseas rate, stipend of £19,668 per annum and Research Training Support allowance (RTSG)
Number of awards
Tuition fee status
Mode of study
Available to applicants in the following departments
- Electrical and Electronic Engineering
- Applicants are expected to have a First Class or Distinction Masters level degree, or equivalent, in a relevant scientific or technical discipline, such as computer science, mathematics or engineering.
- Applicants should also meet the minimum requirement as outlined in the guidance on qualifications.
- Applicants must be fluent in spoken and written English.
- Good team-working, observational and communication skills are essential.
- Experience in one or more of the following areas is desired: machine learning, deep learning, mathematical modelling, and software engineering.
Please note: This scholarship is not available to continuing students.
Application processTo Apply, please choose Electrical and Electronic Engineering Research Program and Intelligent Systems and Networks Group then indicate Dr Chen Qin as a potential supervisor when making the application. Early applications are encouraged. The post is preferred for candidates who can start in early 2023. For further details of the post, please contact Dr Chen Qin at firstname.lastname@example.org. For queries regarding the application process, please contact Emma Rainbow at email@example.com.
Additional informationApplications are invited for a PhD studentship in the field of machine learning in medical imaging, which will be jointly hosted by Department of Electrical and Electronic Engineering and the College's new I-X initiative. Home and Overseas applicants are eligible for this studentship. It is especially targeted at PhD applicants with an interest in artificial intelligence and healthcare. Prospective students will also join the Biomedical Image Analysis Group.
The PhD research will explore the important topics of machine learning solutions for improving medical imaging workflow. Particularly, the research project will focus on investigating advanced deep learning approaches for inverse problems. It will develop approaches that can incorporate explicit prior knowledge into deep learning methods for data-efficient and interpretable learning. The aim of the research is to combine the best of knowledge-driven and data-driven approaches for inverse medical imaging problems, such as image reconstruction and image registration. The research is at the intersection of artificial intelligence and healthcare and has the potential to make significant positive impact on society by improving patient care through better diagnosis and treatment.
The Department of Electrical and Electronic Engineering has a long and proud history of world-class research and innovation and is at the forefront of tackling the most urgent global challenges in energy, healthcare, smart technology, and communications. It ranked the 1st in the UK (Engineering) in REF 2021 based on the proportion of world-leading research (4*).
I-X is a new collaborative environment for research, education, and entrepreneurship across the areas of artificial intelligence, machine learning, data science, statistics, and digital technologies. The goal of I-X is to realise new models for research, education, and entrepreneurship that go beyond traditional siloes imposed by academic disciplines, thus forming a blueprint for the university of the future. I-X benefits from a strategic investment by the College, which includes new facilities on Imperial's White City and South Kensington campuses. For more information about Imperial-X, please visit the I-X website.
If you have any additional questions, please contact us at firstname.lastname@example.org.