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Field
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PhD students, you will further perform human testing of several prototype devices developed at Delft University of Technology and you will cleverly review and interpret the measurement data
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quality that is not visible in blood or clinical characteristics. By combining the results of AI-driven image analysis of histological samples conducted in this PhD project with biomarker data and outcome
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representations. In this project, you will substantially improve quantitative magnetic resonance imaging (MRI) image quality using deep learning approaches. Quantitative MRI allows healthcare providers
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aims to study how the brain processes pictures and sequences of pictures, like in comics. These PhD positions will study how sequences of images combine images together into hierarchic relationships
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. These results will provide essential information for anaerobic process design in recycled cardboard industry under water-saving scenarios. This PhD project comprises the following activities: Sorption kinetics
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chip prototype, improving performance and durability in automotive applications. Specifically, this PhD project focuses on memristive materials as electronic realizations of the hysteron concept
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processes. In this project, we will leverage the advanced voltage imaging in larval zebrafish to investigate how intrinsic plasticity reshapes neuronal behavior. Your job Traditional electrophysiological
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Image Analysis Group (DIAG) at Radboudumc. We develop, validate and deploy novel medical image analysis methods, usually based on the newest advances in machine learning with a focus on computer-aided
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simultaneous stimulation of these processes increases aggregate clearance. This project will employ a combination of advanced cell biology, molecular biology, live-cell imaging, and proteomics approaches. Your
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holders, setting requirements on data quality and measurement conditions. Together with cardiologists, supervisors and colleague PhD students, you will further perform human testing of several prototype