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innovative methods for processing and analyzing 7Tesla MRI images of different modalities and formats (NIFTI, DICOM, etc.) using machine learning and artificial intelligence techniques. These methods will be
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equipment. This position involves both technical and research support responsibilities. The successful candidate will contribute to method development, target and non-target analysis of environmental
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equipment. This position involves both technical and research support responsibilities. The successful candidate will contribute to method development, target and non-target analysis of environmental
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on estimated movements using eDCCs. The research will focus on data simulated using the Monte Carlo method and real data from clinical SPECT scanners with a parallel collimator, such as those available at LUMEN
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physics-informed and physics-ML hybrid approaches that integrate domain knowledge with data-driven methods to advance hydrological process understanding and prediction. Conduct multimodal, multiscale data
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correlations. This study will be conducted in collaboration with specialists in microscopy, RX and optical methods, and modeling (DFT/molecular dynamics). - Modeling the NMR parameters of selected lithium
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jurisdictions utilizing land use-value assessment estimates. Duties include, but are not limited to: development of computational methods, maintenance of current models and data sets, identifying and testing
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, mathematics or related majors Job Description: The Postdoctoral Researcher will play a key role in developing and applying cutting-edge AI methods to analyze large-scale clinical datasets, including electronic
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: Initiate and maintain cell cultures Prepare and maintain biological stocks Maintain proper lab and experimental records, both digital and hard copy Test, optimize, troubleshoot new and existing methods and
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are non-Lorentzian field theory and gravity (e.g. Galilean, Carrollian, and Lifshitz geometries), non-AdS extensions of gauge/gravity dualities (e.g. non-relativistic holography, Carrollian perspective