101 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "The Institute for Data" positions at Aalborg University
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environments This PhD project investigates the use of digital technologies (environmental sensing, user feedback loops, computer vision, machine learning) and theories of human perception and behavioral nudging
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research activities and to Aalborg University’s long-standing tradition of Problem-Based Learning, which encourages student engagement through project work and real-world analytical challenges. We strive
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on working in Denmark and at AAU at https://www.en.hr.aau.dk/information-and-guidance Salary and terms of employment The employment is in accordance with the Ministerial Order on the Appointment of Academic
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problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading fundamental and applied research within communication, networks, control
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network of collaborators. Read more about PREDICT: https://www.predictibd.dk/ About the Department of Clinical Medicine: The Department of Clinical Medicine provides research-based teaching across all
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problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading fundamental and applied research within communication, networks, control
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the Human-Centered Computing section,which focuses on designing, developing, and applying interactive computing technologies. More information can be found on our website: https://www.cs.aau.dk/research/hcc
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at the intersection of AI, RF, and wireless communication. Your main tasks include developing machine-learning methods for wireless interference detection, mitigation, edge intelligence, and applying AI to optimize RF
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of POLSAFE (see profile: https://vbn.aau.dk/da/persons/jajh/ )The research team will consist of two postdoctoral researchers working closely together with the principal investigator and a research assistant
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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