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a world-class doctoral training programme in risk assessment, resilience engineering, and smart technologies. Its scientific vision targets: (1) the development of a holistic multi-hazard risk
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student projects and BSc/MSc theses Your Profile: Master’s degree in physics, electrical/electronic engineering, computer science, mathematics, or a related field Strong background in machine learning
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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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a world-class doctoral training programme in risk assessment, resilience engineering, and smart technologies. Its scientific vision targets: (1) the development of a holistic multi-hazard risk
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/NL. The successful candidates commit to actively participate in networking including regular research visits to the partner laboratories. Requirements: university degree in chemistry or physics and
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in physics, electrical/electronic engineering, computer science, mathematics, or a related field Strong background in machine learning, particularly deep learning and optimization methods Excellent
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of Electrical Engineering and Computer Science School of Art and Design Course language German and English Financial support No Structured research and supervision Yes Research training / discussion Yes Career
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26 Aug 2025 Job Information Organisation/Company Helmholtz Zentrum Hereon Research Field Engineering » Mechanical engineering Geosciences » Other Researcher Profile First Stage Researcher (R1
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partners across Europe to deliver a world-class doctoral training programme in risk assessment, resilience engineering, and smart technologies. Its scientific vision targets: (1) the development of a
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or replace established methods from computational engineering and computer simulation (such as the finite element method) to represent and exploit relationships along the composition-process-structure-property