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combination of in-situ and remote sensing observations, as well as climate and snow models of varying complexity, the impact of blowing snow on local and regional scales. The PhD candidate will produce mass
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complexity, the impact of blowing snow on local and regional scales. The PhD candidate will produce mass balance simulations that support estimates of snow distribution for biodiversity and ecosystem
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the Department of Computer Science at UiT The Arctic University of Norway. HDL’s mission is to build and experimentally evaluate the systems, methods, and tools needed to analyze and interpret complex
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including, high resolution 3D and 2D seismic, sub-bottom profiler, regional 2D seismic and petrophysical logs; infer complex Earth system process understanding, including changes in current patterns, glacial
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of past warm periods in diverse geophysical datasets including, high resolution 3D and 2D seismic, sub-bottom profiler, regional 2D seismic and petrophysical logs; infer complex Earth system process
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, capable of synthesizing and expressing complex ideas clearly. Emphasis will be placed on personal and interpersonal qualities. We offer (decide on what is relevant for the position – add and remove) An
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realistic settings referring to statistical and system characteristics in the real world contrary to an ideal learing setting. The candidate will contribute to understanding how neural networks extract
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the following criteria will be emphasised: submitted scientific work and your personal skills for completing the project within the time frame international experience and network qualifications within the areas
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characteristics in the real world contrary to an ideal learing setting. The candidate will contribute to understanding how neural networks extract the most relevant information of the data to make a prediction
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the European Commission, and is entitled to use the HR Excellence in Research (HRS4R) logo. The University is also a member of the EURAXESS network, which contributes to good working conditions for mobile