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                , leveraging modern approaches from environmental seismology and machine learning. It will involve: Collecting continuous underwater acoustic records at multiple locations throughout the Lagoon (records several 
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                , the scattering geometry can be reconstructed mathematically (this is called inverse scattering). This requires both sophisticated mathematical models and efficiently implemented algorithms. In the case of wafer 
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                Max Planck Institute for Solid State Research, Stuttgart, Hamburg, Halle, Dresden | Dresden, Sachsen | Germany | 22 days agohas an open call for multiple fully funded PhD student positions. Deadline for submission of your application is December 10th 2025! Five Max Planck Institutes (Dresden, Hamburg, Halle and Stuttgart 
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                the systems-ML stack. This makes a cohort-based programme vital, treating ML Systems as a holistic discipline. Cohort interaction, and integration, give students real experience across multiple systems 
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                University Hospital, Duke Regional Hospital, Duke Raleigh Hospital, Duke Health Integrated Practice, Duke Primary Care, Duke Home Care and Hospice, Duke Health and Wellness, and multiple affiliations. Summary 
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                University Hospital, Duke Regional Hospital, Duke Raleigh Hospital, Duke Health Integrated Practice, Duke Primary Care, Duke Home Care and Hospice, Duke Health and Wellness, and multiple affiliations. Summary 
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                Max Planck Institute for the Physics of Complex Systems | Dresden, Sachsen | Germany | about 1 month agoPhysics » Mathematical physics Physics » Statistical physics Physics » Chemical physics Physics » Computational physics Physics » Condensed matter properties Chemistry » Physical chemistry Researcher 
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                10 Oct 2025 Job Information Organisation/Company CISPA Helmholtz Center for Information Security Research Field Computer science Mathematics Researcher Profile First Stage Researcher (R1) Positions 
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                training, and interactions among autonomous entities can lead to vulnerabilities. These concerns are amplified in decentralized AI and multi-agent systems, when multiple parties (e.g., human or agent) might 
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                approaches have not been updated in the era of IoT and AI. The overarching aim of this PhD research is to develop a novel data-driven safety assessment and certification framework, leveraging multiple data