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multidisciplinary and multisectoral project? INTROS is the project for you! Find below more information. About INTROS The INTROS project, a Marie Skłodowska Curie Action Industrial Doctorate network (MSCA-DN-ID), is
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solutions for building energy management and in district energy networks, and toolkits of solutions for building and district performance assessment. The combination of computer science with the built
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PhD scholarship in Runtime Multimodal Multiplayer Virtual Learning Environment (VLE) - DTU Construct
Building Information Modelling (BIM) with Structural Health Monitoring (SHM) applying smart sensor networks, Internet of Things (IoT), and resilience-informed design platforms. Furthermore, REUNATECH pro
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identity, behavior, and trajectory. You will extend these models to understand how genetic risk factors alter cell–cell communication networks. Spatial transcriptomics datasets will be used to anchor
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forming a strong multi-disciplinary and international professional network between PhD-students, researchers and industry. Read more: https://wasp-sweden.org/graduate-school/ As a PhD student, you devote
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-Brain inspired Neuromorphic Nanophotonics (InsectNeuroNano). The long-term vision of this project is a novel on-chip hybrid nanostructure platform for energy-efficient, fast artificial neural networks and
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Fraunhofer Institute for Wind Energy Systems IWES | Bremerhaven, Bremen | Germany | about 1 month ago
... Your PhD research focuses on several topics like the development of a novel prognostics model based on the evaluation of sensor data and for this specialized methods. Purpose is the updating of digital
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... Your PhD research focuses on several topics like the development of a novel prognostics model based on the evaluation of sensor data and for this specialized methods. Purpose is the updating of digital
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, spanning diverse application domains such as medicine, energy systems, biomedical systems, neuroscience, and safety and security. We have a wide network of long-standing international collaborators all
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: Develop an event-driven RL algorithm that sparsely updates network state and parameters that will significantly improve energy to-solution efficiency compared to conventional digital accelerators when