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with chemists, engineers, and data scientists will enable the creation of a robust, high-throughput framework for future catalyst and layer development and efficient optimisation. The following topics
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grades in the field of mechanical engineering, material science, physics, computational science or similar, preferably with a specialization in the field of theory and/or simulation Strong understanding
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reliable remote robotic control under network uncertainties, with a strong focus on safety-critical bilateral teleoperation (e.g., tele-surgery). The doctoral research will focus on the development of fault
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(CeRA) specializes in research on male reproductive function. In a multidisciplinary project funded by the Federal Ministry of Research, Technology and Space (BMFTR), we want to research novel approaches
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conventional design methods Your profile: Completed master's degree in computer science, mechatronics, or electrical engineering. Knowledge of AI/ML methods and frameworks (e.g., PyTorch, TensorFlow). Knowledge
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the Job related to staff position within a Research Infrastructure? No Offer Description At University of Siegen, Faculty IV "School of Science and Technology", ETI, Embedded Systems, we are looking
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Materials’ as well as ‘Adhesive Bonding Technology and Surfaces’. Research and development work is focussed on providing customers with reliable and application-oriented solutions. Products and technologies
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results in relevant journals and at international conferences Your Profile: A completed university degree (Master or equivalent) with excellent grades in the field of mechanical engineering, material
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in EUR None Combined Master's degree / PhD programme No Joint degree / double degree programme No Description/content The Konrad Zuse School of Excellence in reliable AI (relAI) offers fully funded
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management of bridge portfolios. You will create tools that transform complex data into reliable insights for infrastructure safety and sustainability. The project is a collaboration between the Engineering