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Field
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design, and/or machine learning in the context of integrated photonics. We are looking for someone who wishes to work theoretically in this field, while still maintaining close contact with experiments
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groups working towards a common goal. For this postdoc project, we seek a dynamic and motivated candidate with an interest in computational electromagnetism, inverse design, and/or machine learning in
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European network, collaborating with major aircraft engine OEMs and leading universities through several EU aviation projects. About the research project The project aims to develop machine learning methods
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methods for creating innovative heat-exchanger geometries with high efficiency and sustainability in mind. You will use open-source machine learning software provided by Meta AI and OpenAI, deployed
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Research Infrastructure? No Offer Description This position offers a unique opportunity to work at the intersection of statistical machine learning, control theory, and transport safety, in collaboration
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This position offers a unique opportunity to work at the intersection of statistical machine learning, control theory, and transport safety, in collaboration with researchers at Chalmers and the
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the Division of Data Science and Artificial Intelligence and the employment is with Chalmers University of Technology. The division’s research spans from foundational machine learning theory to applications
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academic research, learning and outreach. We provide a competitive advantage by linking our top-level international and interdisciplinary academic performance in the areas of material science, nanotechnology
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intelligence, machine learning, data science, applied mathematics, or a closely related field, awarded no more than three years prior to the application deadline*. Documented research experience in machine
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mathematics, data science and machine learning for image recognition. Moreover, you will develop methods and software that will allow new characterization of nanoscale materials. Therefore, your research will