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methods may include physical models, multivariable analysis, self-diagnosis, and AI algorithms. Given the importance of long operating times for underwater sensors, energy-efficient processing is central to
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other PhD projects within SFI Smart Ocean. These methods may include physical models, multivariable analysis, self-diagnosis, and AI algorithms. Given the importance of long operating times for underwater
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with algorithms, numerical methods, signal processing and dynamic system modeling Experience from or formal training within analysis and processing of large data sets, signal processing is mandatory
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Nordisk and for the time being a part of the project «Towards personalized therapies in childhood diabetes: Role of rare genetic variants for diagnosis and treatment». The project has temporary financing
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with Diarrhea,' which is funded by the University of Bergen. About the project/work tasks: This PhD position will examine genetic variation in collected Cryptosporidium isolates as well as inflammation