73 machine-learning "https:" "https:" "https:" "https:" "https:" positions in Denmark
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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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mathematical, statistical, and machine-learning-based analysis of complex data sets, such as hypothesis testing, supervised/unsupervised learning, linear models, etc. Experience with atlas-scale single-cell data
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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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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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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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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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provide the possibility for the student to work with LLMs and machine learning. Your competencies Interest in learner centered technology design, in particular how AI systems can scaffold reflection, agency
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to be 10 million by the year 2050 if new approaches are not undertaken. By joining forces in artificial intelligence (AI), machine learning (ML), chemistry and molecular biology, we intend to develop new
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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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-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