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, or probabilistic modeling, and be proficient in Python and modern machine-learning frameworks (ideally PyTorch). Experience with single-cell transcriptomics, epigenomics, proteomics, spatial omics, or multimodal
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research agenda using advanced quantitative methods—such as machine learning, computational modeling, big-data analytics, and wearable technologies—to study tourism, hospitality, and/or human performance
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PhD Research Fellow in ML-assisted reservoir characterization/modelling for CO2 storage (ref 290702)
strong machine learning and numerical modelling background to add knowledge on the impact of geological heterogeneity and subsurface environments (e.g., depth, exhumation, temperature, pressure) to de-risk
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from Hi-C and Capture Hi-C experiments. Have experience developing graphical user interfaces (GUIs). Candidates with knowledge or experience in machine learning methods will be prioritized. Successful
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of physics- informed machine learning and deep learning, with applications to inverse problems in scientific imaging and the modeling of complex physical systems. The overall goal is to integrate the knowledge
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development in topics such as computer vision, audio signal processing, machine learning, deep learning, and/or sensor systems. Experience in collaboration and technology transfer to partners outside
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the Job related to staff position within a Research Infrastructure? No Offer Description Job Purpose As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our
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Location Lexington, KY Grade Level 12 Salary Range $62,400-111,634/year Type of Position Staff Position Time Status Full-Time Required Education PhD Click here for more information about equivalencies: https
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, early detection of degradation, and residual life prediction. The program integrates physical modeling, machine learning, and data fusion techniques to optimize predictive maintenance, reduce operating
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. The University of North Georgia is currently accepting applications for a Data Science Intern - Institutional Student Worker. This position will: Learn how to apply statistical and machine learning techniques