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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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addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying
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, particularly NaTech (Natural Hazard Trig-gering Technological) events. REUNATECH is a Horizon Europe Marie Skłodowska-Curie Doctoral Network that aims to educate and train the new generation of Doctoral
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consumers. You'll gain deep interdisciplinary experience—combining multiple data layers and approaches including bioinformatics, machine learning, food safety management, regulatory science, genomics and user
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applicants will work as part of the Groeien met Groen Staal (GGS) programme, which aims to make the Dutch steel sector CO₂-neutral by 2050. Steel is crucial to modern society and plays a significant economic
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The successful applicants will work as part of the Groeien met Groen Staal (GGS) programme, which aims to make the Dutch steel sector CO₂-neutral by 2050. Steel is crucial to modern society and plays a significant
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Multiple PhD Scholarships available - Cutting-edge research at the frontiers of Whole Cell Modelling
Multiple PhD Scholarships available - Cutting-edge research at the frontiers of Whole Cell Modelling Job No.: 683222 Location: Clayton campus Employment Type: Full-time Duration: 3.5 to 4-year fixed
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Neurosciences » Neurology Economics » Social economics Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Norway Application Deadline 21 Sep 2025 - 23:59 (Europe/Oslo) Type of Contract
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that shapes society Through robust and close interaction with the world around us – globally, nationally and locally – we shall be instrumental in building a society based on knowledge, skills and attitudes. Do
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. The high-level goal of the project is simple: to use anatomical knowledge and existing knowledge as training data for deep neural networks (instead of manual annotations). The research will be conducted