26 linked-data "https:" "https:" "https:" "https:" "https:" "https:" "https:" "OSU" PhD research jobs in Denmark
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with instructors and students to analysing multimodal learning data (e.g., individual as well as collaborative verbal interactions, student gestures, task and activity sequences) and evaluating long
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Southern Denmark. The Department of Green Technology at the University of Southern Denmark invites applications for a three-year PhD position in data-driven critical raw material supply chain
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, distinguishing local and regional trends. The necessary samples and data have been collected in recent years during expeditions to the area, and include numerous sediment cores, acoustic surveys of the
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One or more PhD positions in Using Large-Scale Data to Improve Precision Medicine in Psychiatry Apply Vacant position One or more PhD positions in Using Large-Scale Data to Improve Precision Medicine
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contribute substantially to publications and the position will involve a variety of tasks, e.g., philosophical analysis, research design development, data collection, analysis, and if relevant dissemination
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DTU Tenure Track Assistant Professor in Surface Physics and Catalysis for Sustainable Energy Solu...
well as to allow video information to be shared for both marketing, analytics and editorial purposes. By accepting optional cookies, you consent to the processing of your personal data - including
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, developing causal identification strategies in observational data, and conducting human experiments with AI chatbots as adaptive dialogue interventions. The postdoc will lead the empirical work on work
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that include collaboration partners from both academia and industry. Further information For information about the CAPE research center, please see https://www.sdu.dk/en/forskning/cape For
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where hygienisation and other biosecurity barriers interrupt them. Using a risk-informed longitudinal design, the candidate will sample linked compartments including incoming biomass vehicles
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We are seeking a postdoctoral researcher to join an interdisciplinary team developing deep learning models for antimicrobial resistance (AMR) detection directly from MALDI-TOF mass spectrometry data