31 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" "Univ" Fellowship positions at UiT The Arctic University of Norway in Norway
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sheet evolution, methane hydrate fluxes, or applying machine learning to geosciences to reconstruct glacial histories and project future ice sheet behavior. Please read this interview for more details
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and Language Learning Apply for this job See advertisement The position A postdoctoral research fellow position in the neurocognition of multilingualism and language learning is available in
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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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for more details: https://ic3.uit.no/news/sediments-analogues-past-ice-streams-landscapes Within this research area, you can pursue the research questions and methodologies that you are most passionate about
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of the interactions between glaciers and oceans, with a focus on the European Arctic. Please read this interview for more details on Pedro’s work: https://ic3.uit.no/news/msca-physical-biochemical-modeling Within
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details on Philipp’s work: https://ic3.uit.no/news/polar-marine-ecosystems-msca Within this research area, you can pursue the research questions and methodologies that you are most passionate about – this
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will then integrate those data into climate models. Please read this interview for more details: https://ic3.uit.no/news/postdoc-opportunity-investigate-how-much-carbon-is-stored-beneath-ice-sheets
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be found here: https://uit.no/staffmobility Application Please note that the application will only be assessed based on the information submitted by the application deadline via Jobbnorge . It is
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hazards, enhancing asset protection, maritime security, emergency preparedness, and societal resilience. The project will leverage advanced AI and machine learning techniques to enable predictive risk
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samples. Apply machine learning and deep learning techniques to automate segmentation and quantitative analysis of tomographic refractive-index data from cells and tissue samples. Apply the developed