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optimal control, robust control, distributed control, and model predictive control. A background in power system analysis, dynamics, control and/or converter control is considered a strong advantage
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of millions of combinations of control parameters, determining the optimal values to maximize stability, efficiency, and dynamic performance. The ideal candidate will have experience or an interest in
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cultures. To overcome the present-day challenges of the underlying field interaction with the lossy fluids and cells, machine learning will be used to optimize the resulting electromagnetic solutions
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inspired by the brain’s powerful and energy-efficient processing capabilities. MINDnet aims at addressing the challenge through a holistic optimization - from individual computing devices to the overall
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PhD scholarship in Corrosion Mechanisms of Power Semiconductor Device and Components - DTU Construct
simulation results will be used to propose material and design guidelines for improved environmental robustness, such as optimized Cu pad and gel substrate compositions for IGBTs, and enhanced design
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proteomics workflows for the analysis of circulating tumour cells (CTCs) from small-cell lung cancer (SCLC) patients. You will work closely with MIPrecise partners to implement and optimize molecularly
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: Microphone array processing. Acoustic measurements. Statistics and machine learning. Optimization and inverse problems. Excellent communication skills. Your primary responsibilities will be: Conduct original
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promising solution to support such a demand by getting inspired by the brain’s powerful and energy-efficient processing capabilities. MINDnet aims at addressing the challenge through a holistic optimization
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batteries (RFB), enabling affordable and durable long-duration energy storage. The approach is to use hierarchical structures, i.e., complex material layers that can be optimized to specific battery
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” funded by the VILLUM FONDEN. The overall aim of the project is to introduce microstructural engineering to the field of additive manufacturing (AM) of metals. This is to set the stage for optimizing metals