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, machine learning, and information-theoretic approaches to achieve robust, non-intrusive security for the ever-expanding IoT landscape. Feature Engineering for Encrypted Traffic: It is crucial to identify
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/or modelling is essential. Experience in machine learning, computer vision, and computer programming is desirable. In addition, applicants should be highly motivated, able to work independently, as
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-chemical-physics/ ) led by Prof. Alexandre Tkachenko at the Department of Physics and Material Science, we are looking for a PhD candidate to perform molecular dynamics simulations of different genetic
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energy; thereby minimising farming’s environmental impact. AI machine learning offers a new expedient method of developing control systems for tasks that would be difficult to manage using classical
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use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and
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, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction
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, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks Requirements: excellent university degree (master or comparable) in computer engineering or electrical
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: Prof. Diana Göhringer (Chair of Adaptive Dynamic Systems) Terms: 100% of the full-time weekly hours Tasks: The PhD student will be responsible
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of robotics, electromobility and autonomous driving. We offer advanced PhD courses where we extend the fundamentals in optimal control, machine learning, probability theory and similar. The research and
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Research theme: Fluid Mechanics, Machine Learning, Ocean Waves, Ocean Environment, Renewable Energy, Nonlinear Systems How to apply: How many positions: 1 Funding will cover UK tuition fees and tax