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Are you fascinated by electromagnetic modeling and numerical problem solving? Do you want to contribute to the development of state-of-the-art metrology for integrated-circuit production
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accuracy requires high spatial and temporal resolution, which is time-prohibitive and therefore impractical for large parts. This project therefore aims to develop numerical methods that enable the efficient
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accuracy requires high spatial and temporal resolution, which is time-prohibitive and therefore impractical for large parts. This project therefore aims to develop numerical methods that enable the efficient
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, which is time-prohibitive and therefore impractical for large parts. This project therefore aims to develop numerical methods that enable the efficient simulation of the LAFP process while accounting
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fascinated by electromagnetic modeling and numerical problem solving? Do you want to contribute to the development of state-of-the-art metrology for integrated-circuit production? Information Integrated
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understandable explanations from machine learning models. We will achieve this together by creating the first mathematical framework for explainable AI and developing new explanation methods. This will involve
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methods. This will involve using tools from mathematical machine learning theory to prove mathematical guarantees about the performance of such new explanation methods, as well as programming to test out
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written communication skills in English are required. Other advantageous qualities include experience with coding (Python\Matlab) and numerical methods, as well as familiarity with concepts in complex
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meter with a non-insulating pipe wall. The research will use existing MHD direct numerical simulations to investigate the flow physics. You will also construct a prototype to test the performance using
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of turbulent pipe flows. In this project you explore novel fundamental approaches of an EM flow meter with a non-insulating pipe wall. The research will use existing MHD direct numerical simulations