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related field. The ideal candidates will have experience in one or more of the following topics: deep learning for image and point cloud data processing, deep learning for time series data prediction
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position is part of Professor Lehdonvirta’s Aalto-Oxford joint research group, titled the Digital Economic Security Lab (DIESL) . The multidisciplinary lab comprises both social and computer scientists. The
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. Research Environment The project is in collaboration with two partners: (i) IDCOM at the University of Edinburgh, which develops theory, algorithms and hardware for the next generation of signal processing
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Wide Data-Driven Circular Economy of Industrial Robots”. The candidates are expected to have experience with robotics, artificial intelligence, and digital twins. We are looking for candidates who can
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Wide Data-Driven Circular Economy of Industrial Robots”. The candidates are expected to have experience with robotics, artificial intelligence, and digital twins. We are looking for candidates who can
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: Performs specialized research techniques and procedures related to phenotypic characterization of cardiovascular disease using available signal-based and imaging techniques. Compiles and analyzes data using
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, electrical engineering, experimental physics, or a related field Strong programming and signal processing skills, with experience in Python and/or MATLAB Demonstrated ability to work independently and
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role – from microscopes to telescopes, but also for advanced lithography. For the next-generation “hyper-NA” lithographic tool of ASML, the demands of keeping the wafer surface at the focal point
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microscope (HS-DAFM) control software and signal processing circuits. These systems are critical for capturing high-quality nanotexture images from skin samples collected across five countries and four
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combine large-scale data, computational methods, and clearly articulated social-science theories to improve our understanding of society. Recent advances in machine learning, natural language processing