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integrated circuits for next-generation UOWC technologies. As a participant of the project, you will become part of a team at DTU with expertise in design, simulation, nanofabrication, characterization, and
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capability to model complicated magnetic systems for two reasons. First, all magnetic sources in a simulation interact, leading to computational resources scaling with the number of sources squared – which is
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co-simulation platforms (e.g., TRNSYS-Python) Implement and test AI-enabled smart energy management strategies in real-world settings Conducting in situ measurements, including planning, setting up
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tolerant microstructures. The work will be based on experimental characterization guided by advanced AM simulations. The latter being the responsibility of other participants of the MicroAM project
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research assistants, postdoctoral researchers, and academic staff to develop cutting-edge methodologies. The research is cross-disciplinary, combining advanced quantitative analysis, simulation, and systems
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Foundation Classes (IFC), and linked data Sensors as part of Internet of Things (IoT) and integration of sensory information in simulation models during run-time Data processing, incl. artificial intelligence
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localized and delocalized mechanisms that dynamically alter the detrapping and recombination probabilities. The aim of this project is to overcome these limitations by developing a Monte Carlo simulation
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, the proximity effect, and the fringing effect is familiar with the simulation tools such as Ansys (Maxwell), or COMSOL is target-oriented, structured thinking, eager to learn new things, and ready to think
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Job Description Are you passionate about multi-physics modelling and complex data analytics in advanced manufacturing? Join us in our groundbreaking project to develop state of the art simulation