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the development of efficient algorithms and codes for multilinear algebra, with a particular focus on the use of innovative parallel programming models and tools. In the context of this task and as part of the Exa
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learning algorithms that are focused on human behavior modeling related to video classification using deep learning networks for end-users. Work with other team members to develop and maintain software
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the communication system for prototypes of the autonomous monitoring system for invasive wasp species (Asian hornet); (2) to support the programming of AI algorithms for image recognition; (3) to develop the web
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to the development and implementation of approaches that interface with living systems through novel materials and algorithms, electric and magnetic fields, ultrasound, optics and targeted radiation, microfluidics
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Science Programs, and MS in Computer and Information Science (https://cse.aua.am/ ) invite applications for a full-time faculty position in Machine Learning at the rank of Assistant Professor, starting in
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algorithms, together with innovative methodological approaches for the clustering/tiling/thinning/sparsening of complex apertures. Where to apply Website https://lavoraconnoi.unitn.it/incarichi-di-ricerca
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role in supporting research design, algorithmic development, data analysis, and coding tasks across CTED’s interdisciplinary projects. Working under the direction of the Principal Investigator (PI), Dr
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: Python programming Bash programming Familiarity with genomic data Notions of algorithmics Experience with back or front-end web development is a plus Soft skills : team spirit ease in communication
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the activities of GT3. The initial phases will focus on studying the ideal frameworks for creating the IT platform and developing AI algorithms for data analysis. In particular, the data storage structure will be
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experimental systems for cryogenic measurements Development of a microwave quantum control & readout stack Development of Python code to operate quantum systems Detailed experimental characterization