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We have 35 Artificial Intelligence (medical engineering) PhD Projects, Programmes & Scholarships

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Artificial Intelligence (medical engineering) PhD Projects, Programmes & Scholarships

We have 35 Artificial Intelligence (medical engineering) PhD Projects, Programmes & Scholarships

Development of a Low-Cost Autonomous Device for Colorectal Cancer Screening and Treatment

We are excited to announce a fantastic opportunity to join our dynamic team at the Endorobotics Lab, led by Dr. Luigi Manfredi, in the School of Medicine at the University of Dundee. Read more

15 Fully Funded PhD Scholarships in Engineering, Informatics and Cognitive Science

Outstanding applicants are invited to apply to our range of 15 fully funded scholarships. For September 2024 entry, these scholarships are in the fields of Engineering, Informatics, and Cognitive Science. Read more

Doctor of Engineering (EngD) - Image capture and multimodal AI for interactive radiology assistance (Canon Medical and University of Edinburgh)

  Research Group: CDT in Applied Photonics
The EngD is an alternative to a traditional PhD aimed at students wanting a career in industry. Students spend about 75% of their time working directly with a company in addition to receiving advanced-level training from a broad portfolio of technical and business courses. Read more

Controlled Synthesis of Virtual Patient Populations with Multimodal Representation Learning

This project invites PhD candidates who are interested in developing generative models that can deal with complex multimodal patient data, contributing to safer, better and faster innovations of medical products via in-silico trials. Read more

AI Powered Personalized Virtual Heart Modelling

Supervisory Team: Dr Lei Li, Prof. Age Chapman. Project description. In this unique PhD project, we aim to develop advanced AI models for creating cardiac digital twins, i.e., virtual heart models. Read more

Medical Image Analysis using Deep Learning

Medical Image Analysis aims to extract information from available visual modalities such as Magnetic Resonance Imaging (MRI), Computed Tomography (CT) and Ultasonography (US) to detect conspicuous structures, quantigy their properties, evaluate the effectiveness of treatment or diagnose a condition. Read more

Exploration of deep learning based generative adversarial networks (GANs) to mitigate bias in the evaluation of medical images among diverse population and disease sub-groups

Medical image analysis using Deep Learning models involves training on progressively larger datasets. Homogeneity of data within the training set, particularly in its representation of diverse population sub-groups and various disease stages, substantially influences model effectiveness. Read more

Computational methods for medical image analysis: Foundation models, Generative models and Multimodal Learning

The field of medical imaging and precision medicine has seen remarkable advancements in recent years, driven by the potential of artificial intelligence (AI) technologies, such as generative models, foundation models, multi-modal learning algorithms, and large language models. Read more

Wearable multimodal sensors at loaded body interfaces to assist remote healthcare

Supervisory Team.   Professor Liudi Jiang. Project description. Millions of people globally suffer from various physiological disorders and thus require long term sometimes lifelong rehabilitation and care. Read more

Lightweight Deep Learning in internet of medical things (IoMT)

These projects are open to students worldwide, but have no funding attached. Therefore, the successful applicant will be expected to fund tuition fees at the relevant level (home or international) and any applicable additional research costs. Read more

Laser-based fabrication of medical diagnostic devices in paper

The focus of our group’s research is the development of user-friendly sensors or devices for affordable and rapid clinical diagnostic testing at the point-of-care (POC) of a patient, i.e., at their hospital bedside or in a care/nursing home, or in ambulance or at home. Read more

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