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Would you like to perform cutting-edge neuroimaging research to improve rehabilitation and quality of life for people with visual impairment? We seek a talented PhD student to develop and validate
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combining high-fidelity computational modelling with artificial intelligence to overcome key barriers in performance. The investigation will focus on optimising core gas exchange and combustion processes
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interference, while ensuring energy-efficient and scalable operation. This PhD project will focus on developing machine learning algorithms to enable robust channel estimation, intelligent user association
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) offering a secure start to the work. This PhD will be an inter-disciplinary, using expertise on meteorology and co-occurring hydro-meteorological hazards (Chen, Hillier, Bloomfield) and insurance industry
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invite applications for a limited number of fully funded PhD studentships at the School of Physics, Engineering and Computer Science of the University of Hertfordshire. This is an exciting opportunity
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group of scientists and medical professionals, mainly focused on innovative clinical imaging methods in breast cancer diagnostics, with a particular focus on cancer screening and artificial intelligence
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Engineering, a 4-years PhD position is available at the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence with the topic of formal verification of distributed systems
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The Informatics Institute at the University of Amsterdam is looking for a highly motivated PhD candidate as part of the NWO-funded research project TACIT (Inclusive Technologies for Access and
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education to enable regions to expand quickly and sustainably. In fact, the future is made here. The Department of Chemistry is opening a PhD position in Chemistry with a specialization in Environmental
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap