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: Microbiome; Bacteria; Microbiology; Metabolites; Nuclear Magnetic Resonance, Mass-spectrometry, Chemometrics; Multivariate statistics; Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL
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systems. Ths position requires a deep understanding of X-ray Absoprtion Spectroscopy and prior experience with methods of machine learning and artificial intelligence. A highly competitive candidate would
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For Finding Class Encoding Patterns”, arXiv, Dec. 2022, URL [ 3] Nicholas J. Schaub et al., “Deep learning predicts function of live retinal pigment epithelium from quantitative microscopy,” Journal of Clinical
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, constraint programming, Bayesian methods, sparse kernel machines, graphical models, and deep learning. Some examples of materials classes of interest for this project are photovoltaic, thermoelectric
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, including research in deep learning for genomics and “explainable AI”, and collaborating with Genome in a Bottle Consortium members and others from companies, academia, and government. [1] JM Zook, et al
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.103341. Deep Learning; Compartment Fires; Real-Time Forecast; Realistic Conditions; IoT Sensors