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Embedded AI, Edge AI, TinyML, and AIoT, that can be documented by a publication record in relevant venues. Solid understanding of state-of-the-art embedded machine learning techniques. Experience in system
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and proposal preparation. Required qualifications: As a formal qualification, you must hold a PhD degree (or equivalent) in computer science, computer engineering, networking, or related fields relevant
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forecasting. You will get the opportunity to participate and influence the development of advanced forecast solutions combining weather forecasts and novel machine learning/statistical forecasting methods
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. Postdocs will be supported in improving their CVs for academic careers. This includes co-supervision of MSc and PhD students, teaching opportunities, and proposal development. You can learn more about ESE
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Electrophysiological signal processing of, e.g., EEG, ECG, EMG, etc. Health data science, incl. modern machine, and deep learning methods, Cloud-based platforms like MS Azure or Google Colab Health data standards, like
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analysis Close collaboration with an interdisciplinary team. Research and teaching efforts at a section and departmental level as appropriate and relevant (e.g., teach and supervise MSc and PhD student
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spatio-temporal regularization, discrete tomography, low-dimensional latent representations and machine learning. The ultimate aim is to reduce the carbon footprint for the construction industry and enable
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. theses at the interface between structural engineering and machine learning. You will disseminate your research through peer-review publications and participation in international conferences. You will
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thermomechanical process simulations such as casting and welding. The research activities at SDU-ME spans widely from fluid mechanics, condition monitoring, machine learning, fatigue, maritime structures
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University is known worldwide for its high academic quality and societal impact. The Department of Electronic Systems employs more than 200 people, of which about 90 are PhD students, and about 40 % of all