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with researchers at DTU and KTH, you will help develop an integrated decision-support system that: Uses real-time sensor data and AI models to assess risk scenarios. Dynamically recommends optimal
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conditions in dynamic and international research environment. Principal supervisor (PI) is Professor Pernille Bjørn, Department of Computer Science, pernille.bjorn@di.ku.dk The PhD programme Option A: Getting
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for dynamic risk evaluation; (3) the advancement of risk-to-resilience methodologies; and (4) the establishment of digital twin-based resilience frameworks for CI, HTI, and urban environments. The network
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of digital environments utilizing real-time data for dynamic risk evaluation; (3) the advancement of risk-to-resilience methodologies; and (4) the establishment of digital twin-based resilience frameworks
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Job Description The Loft Group at the Functional Genomics & Metabolism Research Unit, Department of Biochemistry and Molecular Biology, University of Southern Denmark, invite applications from
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that merge thermo-fluid dynamic laws, deep learning, and experimental data. A central goal is to overcome current limitations in TES operation and optimization, enabling discovery of new high-performance and
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of non-traditional sensors for pavement monitoring, such as accelerometers, gyroscopes, and dynamic tiltmeters. Lastly, parametric investigations will be carried out with the validated code, utilizing as
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projects partners. This requires good communications skills but also allows you to co-operate with leading European research institutes. Responsibilities and qualifications You will be part of a dynamic work
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Molecular & Medical Biology Section. About the Molecular & Medical Biology Section at the department The Molecular & Medical Biology Section conducts research in basic and translational science of molecular
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of thermodynamic modelling, process simulation is an advantage. For applicants to the PhD position, you must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent