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CO2 capture from the atmosphere. Your objectives will include to: Develop new optimization and/or machine-learning based reconstruction and segmentation algorithms to improve image quality in time
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hubs. Control and optimization of power electronics for flexible port energy systems. Modeling, simulation, and experimental validation of port power conversion and electrification solutions. Integration
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Design and Optimization of Biologics. The research program will build on the recent advances in protein design, automation, and multi-parameter optimization and create a closed loop pipeline able
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carriers within defects. The charge transport will be implemented stochastically to mimic nature. A significant focus of the project will be to apply machine learning techniques to optimize the model and
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mathematical and analytical models to predict coil loss, facilitating the optimal design of HPMCs Constructing a large-signal platform to measure coil loss of HPMCs Exploring innovative solutions, such as new
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learning techniques to optimize the model and enable charge transport simulations over 20 orders of magnitude in time. This comprehensive model will allow researchers to study the effects of crystal size
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for the analysis and optimization of silicon single crystal production. The section for Manufacturing Engineering at DTU Construct is seeking two highly motivated postdocs for a project on multi-physics, multi-scale
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engineering, and process optimization in a collaboration between photochemists at DTU Chemistry and photonics engineers at DTU Electro. It is funded for a three-year period by the Novo Nordisk Foundation
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modelling, control, and energy system integration. The position is a full-time post doc position. Responsibilities and qualifications Your overall focus will be to strengthen the department’s competencies
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one of the life science industry’s biggest challenges: Closed-Loop Design and Optimization of Biologics. The research program will build on the recent advances in protein design, automation, and multi