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models using cutting-edge language technology. The project involves collaboration with experts from TU Delft, focusing on enhancing the security of machine learning model sharing without compromising data
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and machine learning. Master of Science (MSc) diploma in Transportation, Robotics, Computer Science, Logistics, Operations Research, Industrial Engineering, Applied Maths or any other related field
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. Your home base will be the Mobility in eXtended Reality Lab in the Department of Transport & Planning within the Faculty of Civil Engineering and Geosciences. Our diverse team of researchers, project
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each other. This necessitates a multidisciplinary approach bringing together optimization, machine learning and behavioral modeling methodologies. In FlexMobility we propose a holistic approach to design
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expert knowledge in a reusable format. Numerical Representation, Develop numerical representations of ship designs that are interpretable by machine learning algorithms and suitable for generative ai model
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the first direction, you will develop advanced system identification techniques that combine nonlinear dynamics theory with machine learning tools. The goal is to extract governing equations directly from
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quantitative modeling; Strong expertise in programming, including proficiency in languages commonly used in data analysis and machine learning, such as Python; Excellent verbal and written communication skills
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human perception and cognition. Experience in: experimental methods, computer rendering or VR/XR, programming. Affinity with multidisciplinary work, combining science, art, and technology. Enthusiasm
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these sounds fascinating, then this PhD position is made for you! Information We invite highly motivated students with a strong background in mathematical control theory, and a keen interest in machine learning
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directly with designers, computer scientists, people with disabilities, caregivers, technology developers, and relevant stakeholders through co-design and participatory research. *A related PhD position is