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protocols and have affinity with medical topics. You have knowledge of CT dosimetry and radiation physics. You have good experimental skills and experience with image processing. You have some knowledge in
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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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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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scientists, clinicians, and engineers to push the boundaries of brain imaging and contribute to insights that can improve healthcare practice. Technical PhD Candidate In this role, you will be responsible
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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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excitability, have been shown to be necessary for memory formation. Still, it remains unclear how intrinsic plasticity contributes to memory encoding and alters cognitive processes. In this project, we will
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how intrinsic plasticity contributes to memory encoding and alters cognitive processes. In this project, we will leverage the advanced voltage imaging in larval zebrafish to investigate how intrinsic
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This position is part of the NWO KIC Smart Materials project, Smart Materials for Information Processing, in collaboration with the NanoElectronics (NE) group at the University of Twente and the
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on the development, optimization, and clinical evaluation of new x-ray-based imaging methods. The lab focuses on the use of medical physics approaches to improve image acquisition methods and processing algorithms
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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