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conditions. The in vivo work involves close clinal monitoration of compromised neonatal piglet, and their responsiveness toward a set of interventions. The program also involves a series of laboratory
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broadly cover digital technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip
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) or Machine Learning models. These tools will be integrated with physics-based models of environmental loading (waves and wind) to enhance the accuracy and robustness of the assessment. All components assembled
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medical images and other health data. The group develops and evaluates clinically meaningful decision support tools by integrating health data, domain knowledge, and machine learning. Key objectives include
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at CPPEM (see more below). We are looking for a candidate with a track record within observational research and with experience with machine learning or other relevant data science techniques. The scientific
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Monitoring (LTVEM) in the hospital for management and diagnosis of epilepsy. The technology is built on brain computer interfaces equipped with a Spiking Neural Network (SNN) and aims at early detection