113 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "UNIV" "Univ" positions at Aalborg University in Denmark
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AI-driven creativity with clear environmental performance feedback early in the architectural design process. This phase is characterized by high uncertainty in data availability and design parameters
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unique research infrastructure and lab facilities to conduct world-leading fundamental and applied research within verification and model checking, embedded and cyber-physical systems, data-intensive
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. The support will consist of: organization of chapter meetings (online and not); reference management; figure drafting and data collection; checking traceability, chapter overlaps or inconsistencies; and chapter
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to evolve classical communication networks to support both traditional data and the unique requirements of quantum information systems (https://www.classique.aau.dk). CLASSIQUE will address a suite of
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, Denmark [map ] Subject Areas: Nonparametric estimation, Machine learning methods in econometrics and time series analysis, Statistics for high-dimensional data, Stochastic volatility models Appl Deadline
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with Danish and international industrial partners. More information about the AI RF Sensors group is available at: https://www.es.aau.dk/research/ai-rf-sensors Qualification requirements Appointment as
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. If these problems remain unidentified, they can result in incorrect clinical decisions and poor patient management. In this PhD project, you will collect experimental data describing the changes in blood due to pre
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on development of wave energy and offshore wind. Most of our research is focused around work in our wave flume and basin. Further description of the group may be found here: https://vbn.aau.dk/en/organisations
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(such as heart disease, diabetes, and cancer) using, for example, data from registries and/or biobanks. The research will be performed in close collaboration with Center for Clinical Data Science (CLINDA
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Communication, the Faculty of Social Sciences and Humanities and the Center for Clinical Data Science (CLINDA), Department of Clinical Medicine, the Faculty of Medicine. AI:GENE-XPLAIN develops AI tools