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PhD Stipend in machine learning methods for the analysis of IoT time-series data. At the Technical Faculty of IT and Design, Department of Computer Science, one PhD stipend in machine learning
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The Department of Electronic 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
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of machine learning, and/or ecological modelling. Excellent oral and written English language skills. Strong collaborative skills, team spirit and the ability to also work independently. Experience with field
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analysis utilizing methods rooted in artificial intelligence (i.e. machine learning and deep learning). The analysis will be the basis for developing a predictive model to help select the most optimal method
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machine-learning based methods for analyzing IoT time-series data. Your Competencies: We seek a highly motivated researcher with a PhD in computer science, proficiency in software development, and a strong
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Professorhip grant, which you can learn more about here: https://www.cnap.hst.aau.dk/lundbeck-professorship As a PhD fellow your tasks include: Conduct research under the supervision of senior CNAP staff members
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that aims to redesign how students learn programming through AI-driven, dialogue based, and pedagogically grounded tools. The PhD candidate will contribute to a cross-faculty collaboration spanning the TECH
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for this PhD proposal should have the following qualifications: M.Sc. degree in electrical engineering, mathematical engineering, acoustics, machine learning or similar; Solid mathematical and analytical skills
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machine learning methods for detecting, classifying, and identifying wireless anomalies in real-world radio environments. You will design and experiment with AI-driven approaches for spectrum analysis, work
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Do you want to be part of a young, dynamic research group working on designing the next generation of sustainable energy materials using computational chemistry and machine learning? And do you see