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”, led by Associate Professor Valeria Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case
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Background in probabilistic methods Experience with the application of AI algorithms and probabilistic methods Good programming skills Personal characteristics To complete a doctoral degree (PhD), it is
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of study at all levels. Our subject areas include hardware, algorithms, visual computing, AI, databases, software engineering, information systems, learning technology, HCI, CSCW, IT operations and applied
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life where mother and child live in symbiosis. This relationship however induces multiple symptoms for mothers including nausea, vomiting, bleeding, pain, fatigue and many more. Do you want to discover
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detection and classification algorithms using measured and/or simulated data, such as current pulses from cable faults (breakdown), partial discharges and external noise. In addition to being part of
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of theoretical and applied IT programmes of study at all levels. Our subject areas include hardware, algorithms, visual computing, AI, databases, software engineering, information systems, learning
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of Bergen. About the project/work tasks: Pregnancy is a unique time of life where mother and child live in symbiosis. This relationship however induces multiple symptoms for mothers including nausea, vomiting
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Additional Skills and Experience Experience utilising and integrating multiple methods and multiple kinds of data in their research Proven ability to implement research projects on time and to a high quality
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references Additional relevant documentation of professional knowledge (for example, list of scientific works). If it is difficult to judge the applicant’s contribution for publications with multiple authors
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the applicant’s contribution for publications with multiple authors, a short description of the applicant’s contribution must be included. About The Faculty of Environmental Sciences and Natural Resource Management