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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
quality. Secondly, different machine learning strategies based on traditional supervised learning techniques (e. g. random forest (RF), artificial neural network (ANN)) will be applied using the parameters
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advantages. We will provide the necessary hardware and software for the real-time control of the machine, but the candidate will be responsible for developing and implementing the control algorithms. A working
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supervised deep learning algorithms for 3D laser data from forests Developing self-supervised deep learning algorithms for 3D laser data from forests Expand for a wider variety of downstream tasks focused
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reliable and reproducible measurements across different assays. In this PhD project, you will develop RMPs and reference materials (RMs) for several protein TMs to enable harmonized and reproducible
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, you have gained essentially corresponding knowledge in another way. The applicant is expected to have good knowledge of computer science, mathematics, algorithms, and programming. Knowledge and
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university, the internationally accredited registrar and classification society DNV, and Cancer Registry of Norway. You will be analyzing and developing algorithms for privacy preserving health registry data
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collaboration with the Intelligent Maintenance and Operations Systems (IMOS) Laboratory at EPFL (Prof. Olga Fink). IMOS focuses on the development of intelligent algorithms designed to improve the performance
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a focus on creating an inclusive and bottom-up driven research environment. Our workplace consists of a diverse set of people from different nationalities, backgrounds and fields. As a PhD student
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matter physics, and quantum computing. You will dive deep into the realms of theoretical and computational physics with a focus on the development of algorithms and large-scale numerical simulations. Your
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, quantum networks are slowly becoming a reality. The coordination algorithms that govern their operation are unlike those employed in classical networks, necessitating novel verification approaches. The goal