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. The research focuses on the areas of human-computer interaction and visualization. It involves designing controlled user experiments and applying AI techniques such as reinforcement learning and foundation
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energy-efficient and sustainable transport systems through world-class research in tribology and machine elements. Friction losses in vehicle systems still account for a significant portion of global
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the field of Machine Elements. The main aim of this PhD student position is to strengthen the newly started research on Triboelectrictive nanogenerator (TENG)-based smart lubrication in Machine Elements
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Theory, Department of Environmental and Energy Sciences. Become a part of the team and contributing to research on current and future mobility service usage and attitudes among car and non-car owners
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. Knowledge of PyTorch and hands-on Python programming. Knowledge of machine learning and robotics, or foundation models. Awareness of diversity and equal opportunity issues, with specific focus on gender
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a doctoral student with a strong background in machine learning, mathematics, and modeling, and an interest in biological systems. The successful candidate will join a project to understand and model
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We are looking for a postdoc to join our team at the Division of Computer and Network Systems. Become part of our innovative group and contribute to exciting research in Computer Architecture within
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and Semantic Systems (RSS). The RSS division focuses on research and teaching in AI, Machine Learning, Robotics and Robotic Learning, Human-Robot Interaction, and Natural Language Processing. Together
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. In addition, the following are requirements for the role: Strong programming and quantitative skills, particularly in Python and/or R. Experience in deep learning, machine learning, or large-scale
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machine learning. The project combines methodological research in statistics with applications to large-scale social science data. The successful candidates will have the opportunity to collaborate closely