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Field
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, statistical signal processing, optimization theory, machine learning and artificial intelligence. The candidate is expected to actively participate in experimental work focused on building datasets of channel
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research. The ideal candidate will have experience in conducting and analyzing behavioral experiments, online experiments, physiological recordings, signal processing, statistical analyses, and computational
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, creative, independent, and enthusiastic scientist to further our basic and translational studies of inflammatory bowel disease (IBD). We study disease-relevant cell and organ signaling pathways in IBD
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secondary bile acids have multiple signalling roles in the host and have been implicated in numerous disease states, including inflammatory bowel disease. Inflammatory bowel disease (Crohn’s disease and
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project on a real-time brain-inspired system-on-chip for seizure detection and prediction using EEG signals. We are seeking a motivated postdoctoral researcher to develop high-accuracy algorithms
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are essential, along with a track record of published papers and strong self-motivation. - Prior experience in the areas of machine learning / data-driven methods, signal processing and/or applied mathematics
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contributions to work in climate change, disasters, smart cities, risk regulation, water, human migration and land surface processes related to for example agriculture, forests and landscape fire. We are also
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. This document will provide information of what criteria will be assessed at each stage of the recruitment process. * Please note that this is a PhD level role but candidates who have submitted their thesis and
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novel proteins/antibodies and explore their biomedical applications. Our goal is to utilize these engineered proteins to precisely regulate intracellular signaling pathways, eventually translating
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made from magnetoelectric materials, which transduce wireless magnetic powering signals into local electric signals that can be used to stimulate neurons. Our multidisciplinary group works in materials