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data management and machine learning is also preferred. An interest in energy system topics such as the green transition, sustainable energy systems, digital energetics etc. is preferred. Experience
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(DInSAR). Minute surface uplift and subsidence signals will be automatically detected using machine-learning workflows, enabling systematic, user-independent identification of drainage events every 6–12
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Job Description Are you an established researcher in probabilistic machine learning, with a passion for developing robust, trustworthy, and explainable AI methods for applications in science and
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At the Technical Faculty of IT and Design of the Department of Sustainability and Planning, Copenhagen, a position as Postdoctoral researcher in Geospatial Machine Learning for Predicting Land Use
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physics, HVAC systems, and thermodynamics. Control Expertise: Experience with advanced control strategies and/or machine learning techniques. Digital Engineering Skills: Familiarity with Building
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leading Human-Computer Interaction venues. Your competencies You hold a master’s degree in human-computer interaction, computer science, interaction design, applied artificial intelligence, architectural
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Systems at The Technical Faculty of IT and Design invites applications for PhD stipends or integrated stipends in the field of Machine Learning for Intelligent Hearing Assistance in Complex Acoustic
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-intensive systems, spatio-temporal data management, data analytics, and applications of machine learning, with applications in digital energy and intelligent transport. International evaluations place DESS in
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focuses on the development of secure and trustworthy AI for resource-constrained embedded systems used in power electronics and energy infrastructure. The research will investigate how machine learning
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vision, XR and generative models, specifically for capturing challenging scenarios and training deep learning systems to create better experiences for human users and learners. You will contribute