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Field
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of Data Science is one of Norway’s early dedicated academic environments in data science and applied machine learning. The department combines expertise in machine learning, statistical modelling
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and hardware security assurance for embedded systems by combining advanced side-channel analysis, fault-injection techniques, AI- and machine-learning-assisted analysis, robustness evaluation, and
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 1 month ago
analysis, image analysis, statistical, and machine learning methods, choosing the approach that best fits the scientific question. Investigate systematically what information is contained in imaging data
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to understand how complex biological functions emerge from interactions between individual cells. Where to apply Website https://www.academictransfer.com/en/jobs/362789/phd-learning-interactions-in-co
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field. Strong foundations in machine learning and familiarity with current AI tools and practices. A solid understanding of large language models, in particular their reliability, security, and
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Intelligence and Machine Learning FPGA and Hardware Acceleration Embedded Systems Design Software Defined Radio (SDR) Power Amplifier Modelling and Linearization Specific Requirements Experience in one or more
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available1Company/InstituteDepartment of Computer ScienceCountryNorwayCityTrondheimPostal Code7491StreetHøgskoleringen 1Geofield Contact City Trondheim Website http://www.ntnu.no Street Høgskoleringen 1 Postal Code
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-Physical Energy Systems The PhD position focuses on the development of secure and trustworthy AI for resource-constrained embedded systems. The research will investigate how machine learning models can be
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computational fluid dynamics. • Experience in modeling, uncertainty quantification, or statistical methods. • Experience in data science or machine learning is considered an asset. • Experience with high
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). Desirable assets are: • Machine learning, deep-learning, artificial intelligence, advanced statistical inference; • A solid record of research activities, including relevant publications in international peer