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Project, combined with advanced statistical methods, machine learning techniques and data from wearable sensors. Collaboration with clinicians, data scientists, engineers, researchers and patient
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to positive change in society You can expect numerous benefits , such as public transport season tickets and car sharing, a wide range of sports offered by the ASVZ , childcare and attractive pension benefits
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spanning artificial intelligence, circuit design, computer architecture, and embedded systems engineering. Where to apply Website https://www.academictransfer.com/en/jobs/362502/phd-on-emulation-framework
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
for the position. Preferred selection criteria Experience with machine learning or other relevant AI technologies Scandinavian language skills Previous experience from industry or research in engineer-to-order
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covering the entire energy chain, from resources to the end-user. We look at how energy is produced and used by humans and machines in a sustainable way with regard to health, climate change and the resource
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engineering stimulated by recent developments in machine learning, the project investigates how runners’ shared social identity can influence their movement synchrony, physical load, and interaction with
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that you are particularly suitable for a PhD education. You must meet the requirements for admission to the faculty's doctoral program(https://www.ntnu.edu/studies/phiv ) Very good English skills (both
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strong interest in machine learning/artificial intelligence. You have experience with deep learning. You have experience with reinforcement learning (preferred). You have experience with explainable and/or
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and cooperation. You have a strong interest in machine learning/artificial intelligence. You have experience with deep learning. You have experience with reinforcement learning (preferred). You have
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and cooperation. You have a strong interest in machine learning/artificial intelligence. You have a strong interest in graph-based learning (e.g., graph neural networks). You have experience with deep