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(usually PhD). The Chair of Adaptive Dynamic Systems conducts research in the fields of reconfigurable computing, domain-specific multi- and manycore architectures, networks-on-chip (NoCs), methods and
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/research-groups/CRITIX/ ) headed by Prof. Marcus Völp. The team focuses on critical information infrastructures and cyber-physical systems with the aim to protect our most sensitive and valuable assets. We
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Leibniz-Institute for Plant Genetics and Crop Plant Research | Neu Seeland, Brandenburg | Germany | about 7 hours ago
architecture of important crop traits like grain yield heterosis. In the era of large population size and dense genomic data such as whole-genome sequencing, new algorithms are needed to remove the bottleneck
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Networks, and ICT Services & Applications. Your role Design intelligent agent architectures leveraging large language models (LLMs), planning algorithms, and secure transaction protocols tailored
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A fully funded 3.5 years PhD position in the field of experimental nanoscience at surfaces and molecular imaging of conjugated polymers is available in the group of Prof. Giovanni Costantini at UoB
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resume with professional and technical skills, and exploring the scientific and cultural diversity in Europe and North America? The graduate training program in Scalable 2D-Materials Architectures (2D
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Tenants’ Association. The supervisors represent expertise in: Sustainable architectural design, building transformation and renovation (Prof. Paula Femenías, Chalmers) Sociology with focus on environmental
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architectures, or diffusion models. In close collaboration with clinical partners, you will translate your research into practical, translationally relevant applications, contributing to advances in personalized
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of 1D moiré systems to develop novel device architectures to advance our understanding of strongly correlated quantum systems. The central goal is to fabricate quantum devices hosting heterostructures
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operational employment. This doctoral research will thus leverage the power of graph neural networks – a novel ML architecture, capable of learning fundamental physical behaviour by modelling systems as graphs