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approach will create a unique foundation for advanced data analysis, including AI, machine learning, and statistical modeling, aimed at uncover the key traits that define successful microbial biofertilizers
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and analysis, human-machine interaction, productivity monitoring, and proactive personalized feedback and learning methods (using augmented and/or virtual realities). We seek excellent candidates with
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Communication, Singal Processing, Low Power Electronics, Wireless Sensing, Low-Power System Design, Machine Learning & Edge Inference, Underwater acoustic communication. Furthermore, you have a proven record of
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qualification, you must hold a PhD degree (or equivalent). The successful candidate must moreover exhibit the following professional and personal qualifications: Strong background within machine learning learning
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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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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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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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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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on the modelling and optimisation of PRO systems using advanced Computational Fluid Dynamics (CFD) and Machine Learning (ML) techniques. This role offers an exciting opportunity to contribute to cutting-edge