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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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omics data, and explainable AI (XAI) for the prediction of hepatocellular carcinoma (HCC). Your research will directly contribute to early detection and risk stratification in patients with liver disease
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such risks, and on how to achieve a better use and exchange of existing protocols and data. The project includes the use of Digital Twins to simulate cascading disaster effects, as well as satellite and sensor
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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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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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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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of Defence and other consortium partners (e.g., GKN, ProRail). Information and application Are you interested in joining our team? Please submit your application before 11 October, 2025 and include: A
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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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. Information and application Please apply here before September 30,2025. The application should include: A motivation letter, A CV, summarizing your education, previous work experience, publications, and contact