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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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. PhD Candidate Neuroimaging in Epilepsy Our goal: to leverage advanced Magnetic Resonance Imaging (MRI) techniques (including functional MRI to assess brain network metrics and MR spectroscopy to measure
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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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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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imaging, X-ray tomography/radiography).
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for deployment and operation on a real-world quantum network prototype, build by the Quantum Internet Alliance (QIA) collaboration. The successful candidate enjoys experimenting with different approaches, and is
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project, you will: Investigate muscle physiology using advanced techniques such as MRI-DTI, ultrasound imaging, muscle stimulation, and electromyography (EMG). Perform anatomical dissections on human
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performance programs. As a PhD candidate in this project, you will: Investigate muscle physiology using advanced techniques such as MRI-DTI, ultrasound imaging, muscle stimulation, and electromyography (EMG
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geometry altogether and operate in hyperbolic space. Our lab has published multiple papers showing that hyperbolic deep learning has strong potential for computer vision, from hyperbolic image segmentation
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about how you can contribute to our research, education, impact, and to the team you will be part of. Therefore, we would like to get the best possible picture of your knowledge, insight, skills, and