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of massive galaxies from the primordial Universe to z~2. This project combines a unique JWST dataset with state-of-the art hydrodynamical simulations and machine learning techniques to understand the origins
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Methods in Teaching and Learning in Archaeology. Stapleton, C. & Davies, J. (2011). Imagination: The third reality to the virtuality continuum. IEEE International Symposium on Mixed and Augmented Reality
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/modeling, at the Electrical and Computer Engineering Department, and in collaboration with the Applied Mathematics Department, Santa Clara University. This is an in-person position at Santa Clara University
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or a closely related field (PhD candidates who have submitted or are about to submit their thesis will be considered) Experience of machine learning frameworks (e.g. TensorFlow) Knowledge of Python and C
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employ cutting-edge single-cell and spatial omics technologies with bioinformatics and machine learning to decipher principles of gene regulation underlying cell identity and its disruption in human
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groups working on digital health and wellbeing , network science , computational social science , and various topics in machine learning. You will be working in the research group of one of the PIs
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, clustering analyses, propagating location and other uncertainties...) of mid-ocean ridge catalogs, using standard, Bayesian and machine learning techniques. ⁃ Implement methodologies that improve estimates
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, including development of new computational tools for processing large-scale biospecimen data Creation of novel machine learning frameworks for automated scientific analysis and discovery Design and
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topics. The department has a strong community on related topics: research groups working on digital health and wellbeing , network science , computational social science , and various topics in machine
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in the Earth's outer core, with implications for deep Earth processes [1]. A variety of inverse methods (data assimilation, machine learning, etc.) has been employed to recover the fluid motions in