93 postdoc-in-thermal-network-of-the-physical-building PhD positions at Nature Careers
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algorithms. Graph Neural Networks. The candidate is expected to hold a relevant MSc degree in Computer Science, Data Science, Physics, (Applied) Mathematics, Computational Statistics or another field
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automated, networked mobility, featuring international collaboration with mentors from the USA, Asia, and Europe. TUD and the RTG embody a university culture that is characterized by cosmopolitanism, mutual
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optimize virtual prototypes before building the final physical SAM. While INRIA Lille leads the control design, both teams will collaborate on use-case scenarios and real-world demonstrations to assess
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to climate change. It builds up a national and international network structure in order to integrate existing competences and knowledge, and to link various actors within the complex area of climate change
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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PhD position - Stress-testing future climate-resilient city and neighbourhood concepts (Test4Stress)
builds up a national and international network structure in order to integrate existing competences and knowledge, and to link various actors within the complex area of climate change. The PhD position is
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qualified women to apply for the position. Your tasks develop surrogate models to approximate high-fidelity phase field simulations, incorporating physics-informed loss functions to enhance model accuracy and
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bioinformatics Collaboration with scientists worldwide in strong national and international research network Attractive remuneration Structured doctoral training Have we sparked your interest? Pease send your
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would therefore strongly encourage qualified women to apply for the position. We search for a qualified scientist to investigate the physics of ocean turbulent mixing and its representation in ocean
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the Reinhart-Koselleck programme for innovative high risk-high gain research. Requirements: university degree in chemistry or physics and profound knowledge in computational and theoretical physics/chemistry