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special focus on using advanced CFD simulations to validate novel production concepts' applicability to Aseptic Production(AP). Using simulation tools early in the design process enables fast evaluation
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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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/w) fixed-term postdoctoral position in Simulation and Modelling. The position focuses on designing and implementing the agent-based modeling component of research projects in code, requiring
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machine learning techniques for dynamic energy system modelling Develop advanced optimization algorithms for building energy management and control (e.g., MPC, RL) Develop and evaluate digital co-simulation
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corrosive stimuli/loads thus laying a knowledge-based foundation for design of AM-defect tolerant microstructures. The work will be based on experimental characterization guided by advanced AM simulations
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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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image quality in time-resolved micro and nano CT data. Develop and apply numerical implementations in simulation studies as well as to large experimental micro and nano CT data. Explore multi-modality