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Field
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, signal processing, and data mining A strong background in programming, statistical analysis, and spatial modelling and mapping Highly motivated to work on the subject and eager to work in an
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physics, applied mathematics, machine learning, bioinformatics, biophysics, spectroscopy, image processing, ecological modeling, molecular biology, plant physiology, marine biology or an interest in gaining
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Electrophysiological signal processing of, e.g., EEG, ECG, EMG, etc. Health data science, incl. modern machine, and deep learning methods, Cloud-based platforms like MS Azure or Google Colab Health data standards, like
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-economic losses and damages. However, there is a point at which the additional improvements in human and ecological capital that more adaptation would bring may not be worth the additional investment. Stated
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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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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
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 4 days ago
research programs underway in all areas of modern Chemistry. Chemistry also is a focal point for interdisciplinary research efforts on campus in biological and materials sciences. Minimum Education and
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the internal application process. Welcome to The Ohio State University's career site. We invite you to apply to positions of interest. In order to ensure your application is complete, you must complete
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, Sci Data. 2024 PMID: 38997326 Cruchaga et al., âœNovel early-onset Alzheimer-associated genes influence risk through dysregulation of glutamate, immune activation, and intracell signaling pathways â
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to identifying and interpreting trends in regional-to-local scale signals and extreme events. Large ensembles of climate simulations are a key tool in such applications, but the computational cost of producing