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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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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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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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that also act as green energy producers driving the societal transition towards net zero. In this position, you will build on your expertise in IoT and low-power computer and communication systems to research
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artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics. Our research is rooted in basic
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-based sensor data to enhance the prediction of peatland soil properties and functions. You will focus on leveraging machine learning/deep learning techniques along with explainable artificial intelligence
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-based sensor data to enhance the prediction of peatland soil properties and functions. You will focus on leveraging machine learning/deep learning techniques along with explainable artificial intelligence
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observations, and remote sensing data to assess the impact of global change on ecosystem productivity and sustainability. You will develop novel algorithms to integrate data-driven machine learning and process
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, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks