Kaspar Althoefer
2 months ago
Robotics, Medical Devices, Materials Science Queen Mary University of London in United Kingdom
I am recruiting a fully funded PhD student in soft robotics for medical applications at Queen Mary University of London.
Queen Mary University of London
United Kingdom
Expired
Keywords
Description
A fully funded PhD position is available at Queen Mary University of London in the field of soft robotics for medical applications, as part of the ERC Synergy project EndoTheranostics. The research focuses on developing a next-generation soft robotic eversion colonoscope for minimally invasive diagnostics and therapy, aiming to revolutionize colorectal cancer screening and treatment. The successful candidate will work on the development of an eversion robot capable of addressing the challenges of colonoscopy, including real-time polyp detection, tissue characterization, and autonomous polyp excision.
The project is highly interdisciplinary, combining robotics, medical devices, and materials science, and offers the opportunity to collaborate with leading researchers in the field. Applicants must be UK nationals or residents and hold at least an MSc (or exceptional BEng) in Engineering or a related field. Preferred backgrounds include control, materials, manufacturing, CAD, electronics, computational modeling, and bioengineering.
The position is fully funded for eligible applicants. For more information, visit the project page and apply via the provided link.
Funding
This position is fully funded for eligible applicants. Details on stipend amount and tuition coverage are not specified, but full funding is confirmed for UK nationals or residents.
How to apply
Apply via the provided application link. Review the project details at the linked project page. Contact the supervisor or announcer with questions. Ensure you meet the eligibility criteria before applying.
Requirements
Applicants must be UK nationals or residents. Minimum requirement is an MSc (or an exceptional BEng) in Engineering or a related field. Preferred backgrounds include control, materials, or manufacturing. Experience with CAD, electronics, or computational modeling is desirable. Interest or experience in bioengineering or medical technology is also preferred.
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