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NTNU and the application process here. About the position The Department of Engineering Cybernetics has a vacancy for a PhD Candidate. Foundation models represent one of the most promising avenues
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procedures. The project brings together cardiovascular imaging, generative AI, and computational modeling to develop probabilistic digital twins of coronary arteries. The goal is to create patient-specific
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fees plus an annual tax-free stipend of £21,805 for 3 years full-time. The studentship is funded by the Leverhulme Trust and is part of a grant ‘Rethinking Epidemic Models: Integrating Human Behaviour
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to the development of techno-economic models, and supervise the PhD candidate in all research activities related to energy economics. The researcher will work closely with the principal investigator and the project
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of coronary artery disease and supporting clinical decision-making during catheterization procedures. The project brings together cardiovascular imaging, generative AI, and computational modeling to develop
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Department for Energy Science is seeking candidates who wish to pursue a PhD in Energy Engineering. Your research will focus on developing and applying optimisation models to analyse the future role of
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related to staff position within a Research Infrastructure? No Offer Description PhD Position in NCCR Genesis: On the rise of molecular complexity at the Origin of Life Open PhD position in NCCR Genesis
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into an existing computer model for sediment flux through submarine canyons; and validate the model on monitored submarine canyons. The responsibility of the PhD position advertised here will mainly involve
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composed of specialists in signal processing (i3S Laboratory), computational cardiac modeling (Karlsruhe Institute of Technology, Germany) and interventional cardiology (Nice Pasteur University Hospital and
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Polytechnique de Toulouse (INPT). The PhD student will be part of a group of largely modelling PhD students all trying to make computational fluid dynamics modelling more sustainable in a comprehensive sense