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to provide high-fidelity microclimate predictions at speeds that are much higher than physics-based numerical solvers. We are seeking a Master’s student with a background in Scientific Computing or AI
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geometry), particularly when component variations occur during the process. AI-based process models enable the mapping of these complex relationships while maintaining high inference speeds; however, their
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-parameter and load-pull measurements of various device geometries and epitactical variations technological computer-aided design (TCAD) to analyze breakdown mechanisms benchmark the RF device performance by
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