129 machine-learning-"https:"-"https:"-"https:"-"Linnaeus-University" Fellowship positions in Norway
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- CICERO Center for International Climate Research
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-learning-for-medical-image-analysis Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/293458/phd-research-fellow-in-de… Requirements Research FieldComputer scienceEducation LevelMaster
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Infrastructure? No Offer Description The position A postdoctoral research fellow position in the neurocognition of multilingualism and language learning is available in the Department of Language and Culture
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research activity. In this project, you will develop fundamental machine learning methods and apply them in an interdisciplinary research environment spanning physics, neuroscience and computational science
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, wearable physiological sensing, and machine learning to uncover how factors like fatigue and cognitive workload impact technician performance. Join us to develop predictive models that predict human error
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machine learning and AI techniques to improve prediction of contaminant transport, sediment dynamics, and ecosystem exposure in complex fjord environments. The research will benefit from extensive
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position as Postdoctoral Fellow in law at the UiS School of Business and Law, Department of Accounting and Law. The Postdoctoral Fellow will be affiliated with the research project AUTO-MARE – Autonomous
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modelling tools. This PhD position aims to achieve to develop by the use of automatic picking, rather than manual, travel time picks, and the application of machine learning methods to reliably pick relevant
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. Any appointment is conditional upon submission of documentation confirming completion of the PhD degree. solid programming skills applied to machine learning algorithms, interactive systems, audio and
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topics include (a) AI, machine learning, and large language models for measurement challenges (e.g., for small-sample calibration or for accelerated algorithms), (b) identifying and investigating aberrant
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position (100%, three years) is related to finance and insurance. The theme of the research project will lie within areas such as: simulation and risk modelling using advanced statistical and machine