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Vacancies PhD position on Memristive Smart Materials for Information Processing Key takeaways This position is part of the NWO KIC Smart Materials project, Smart Materials for Information Processing
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Vacancies Postdoc position on Data enhanced physical reduced order Models Key takeaways The position is embedded into a large-scale effort between academic groups in the Netherlands and industrial
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spatial processes; there is considerable potential for further integrating Earth observation data and other spatial data sources into such models. Modelling multiscale interactions with ecological processes
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predict the occurrence of clinical adverse events like delirium, cardiac arrhythmias and pneumonia among elderly after hip fracture surgery. To obtain relevant data for the above described technology
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-guided medical applications, with a focus on advanced robotics. You will work directly with clinical data to design robust, efficient deep learning algorithms that maximize the information extracted from
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contribute to the development and implementation of cutting-edge AI solutions for real-time image-guided medical applications. You will work hands-on with clinical data and build robust deep learning
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cutting-edge multimodal deep learning models that integrate imaging and clinical data to personalize treatment and follow-up strategies. In the Netherlands, around 75% of patients with an abdominal aortic
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, Cascais, Riga, Vilnius, Melsungen, Ciampino, Urla and Rhodes. The PhD project will involve: The use of data analytics (statistical models, machine learning, uncertainty quantification) to monitor and
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in this kind of environment will result in models too large to be handled and too instable to be solved. Data-driven approaches need to be used in addition to enrich the physics-based models
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with your supervisors, but you can work independently, investigating GaN design and pushing the state-of-the-art. Information and application Are you interested in this position? Please send your