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resilience-informed design platforms. Furthermore, REUNATECH promotes trans-disciplinary collaboration via multi-stakeholder platforms, bridging academia, industry, and policy. Through its ho-listic, digital
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decision-making. Collaborate with international partners and contribute to joint research activities. Teach and co-supervise students at different levels in courses and associated projects. Publish and
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results. The ability to work collaboratively in a team with an open-minded spirit, embracing both teaching and learning opportunities. A genuine interest in discussing physics and engaging in thoughtful
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undermine this future. Can you see how Machine Learning, Computer Vision, and Robotics can open up opportunities for autonomously operating agricultural robots? Are you passionate about making agriculture
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. During the project, you are expected to supervise Bachelor and Master students, work in tandem with colleagues and coordinate with collaboration partners, therefore we expect a high degree of project
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Job Description Are you passionate about renewable energy and eager to apply machine learning to real-world challenges? Join our research team at DTU and work on groundbreaking advancements in
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programme at the Faculty of Science . The ideal candidate has a background in or experience with one or more of the following topics: SIMD performance engineering. Machine Learning. Communication-efficient
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experimental research in nanoparticle catalysis using advanced operando electron microscopy This collaborative PhD project between Technical University of Munich (TUM) ( the group of Prof. Barbara A.J. Lechner
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. An external research stay of approximately 3 months in a collaborating institution is a mandatory part of this PhD fellowship position. You will work in close collaboration with experienced researchers and