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of TSN-based in-vehicle networks. These networks carry mixed-criticality traffic and use TSN with multiple traffic shapers and redundant communication. You will investigate methods for runtime analysis
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. Qualifications: You should have (or be close to achieving) a PhD degree. Background within computational methods for inverse problems, ideally tomography. Experience with development of numerical implementations
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the physical chemistry of hydrogen bonds. Your overall focus will be the collection of experimental spectroscopic data and its analysis with quantum calculation techniques and molecular simulation methods. Your
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Job Description If you have a keen interest in computer vision, machine learning, and deep learning, and their application in species identification and automated catch registration
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Job Description If you have a keen interest in computer vision, machine learning, and deep learning, and their application in species identification and tracking to study animal responses to fishing
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Job Description If you have a keen interest in computer vision, machine learning, and deep learning, and their application in species identification and tracking to study animal responses to fishing