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Are you passionate about advancing sustainable mobility solutions? Do you enjoy working at the intersection of artificial intelligence, optimization, and energy management? We invite applications
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/thesis: Industry-/collaboration PhD student in optimized off-road driving in forests Research subject: Soil science Description: We are looking for an industry/collaboration-based PhD student to develop a
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exists for researchers to design and improve animal tests. These limitations hinder the development of optimal experiments and incur cruel animal suffering and killing.The position is two years and you
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and optimize robotic software systems using Python and C++. Create and manage simulation environments tailored to specific robotic applications. Work with ROS (Robot Operating System) for robot control
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application to individually optimized immunotherapy for cancer. The grant covers two postdocs and several PhD students with complementing competences. In this call, we are looking for one PhD student who is
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, optimization) or AI.- Someone who enjoys working in a team, takes initiative, and isn’t afraid to think outside the box.- Someone with excellent grades from BSc and MSc studies, and not afraid of experimental
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the kinetics of enzymatic polymerization processes in biological environments. Expand and tailor enzyme repertoires to optimize functionality and electrode performance. Collaborate within a multidisciplinary and
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optimized immunotherapy for cancer. The grant covers two postdocs and three PhD students with complementing competences. In this call, we are looking for one postdoc who is mathematically oriented, with
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and machine learning to tackle the complexity of force allocation and motion planning under uncertainty and actuator failures. The project combines theoretical research in stochastic optimal control
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of Electrical Engineering . You will be supervised by senior researchers with expertise in robotics, machine learning, automatic control, and optimization. The group leads and participates in numerous