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health monitoring. This will include data collection from volunteers and/or patients. The project will explore data capture with the different sensors including motion capture, radar, and others as
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algorithms, ideally in the healthcare or mental health domain Desirable criteria Track record of successful research grant applications, or attempts to obtain grant funding. Previous development of ML-based
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this, the Fellow will implement a universal design methodology for such fluids of complex rheology, using a Machine Learning (ML) algorithm to be incorporated in a Computational Fluid Dynamics framework. Training
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About Us We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with
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modelling, advanced AI algorithms, and decision-support tool development for various hydrogen technologies-based energy systems. Responsibilities will include programming, analysing and interpreting data, and
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system with integrated sensors. You should hold or be near completion of a PhD/DPhil with relevant experience in the field of robotics, biomedical engineering, information engineering, electrical
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computational frameworks that combine 4D point cloud data, geospatial analysis, and advanced ML/DL algorithms. Integrate dynamic environmental datasets into immersive and interactive prototypes for scenario
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colorectal cancer screening and treatment. They will contribute to the design of AI algorithms for polyp detection, tissue characterization, and visual guidance of robotic intervention. This is a full time
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application. The successful candidate will work at the intersection of multi-disciplinary modelling, advanced AI algorithms, and decision-support tool development for various hydrogen technologies-based energy
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. You have experience in matrix algorithms, data compression, parallel computing, optimization of advanced applications on parallel and distributed systems. An excellent scientific track record proven