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. In this project we will continue development of a new high-throughput method that will speed up and improve such predictions. We will further develop a combination of automated patch clamping and
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of cancer treatment for patients as well as reducing workload for clinicians. Collaborate with experts in AI, data science, and medical imaging to develop integrated solutions. Engage in translational
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psychosis. Key topics may include conceptual development of methods to link multilevel data including EEG recordings as well as symptom-, functioning-, and personal recovery indicators. Study how
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project where we will develop a next-generation diffusion MRI acquisition to map the organization and properties of fibers in the human brain cortex, both post-mortem and in-vivo. You will: Evaluate
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for understanding CHD occurrence, distinguishing three key components: (1) risk factors that drive the long-term development of atherosclerosis, (2) trigger factors that precipitate acute coronary
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-vulnerability model provides a more comprehensive framework for understanding IS occurrence, distinguishing three key components: (1) risk factors that drive the long-term development of atherosclerosis, (2
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bottlenecks in clinical radiology workflows through observations, structured workflow mapping, and close collaboration with clinical staff. Design, develop, and evaluate AI-based and automated workflow