363 structures-"https:" "https:" "https:" "https:" "https:" "University of Lille" Fellowship positions in Norway
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/or in situ hybridisation is a major advantage Experience in work with salmon lice and/or salmon is an advantage Applicants must be able to work independently and in a structured manner and demonstrate
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Proficiency in written and oral English Good knowledge of Norwegian language is an advantage Demonstrated ability to work independently in a structured manner, while also possessing strong collaborative skills
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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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: https://ic3.uit.no/news/interview-retreat-ice-sheets-expose-release-carbon-quantify 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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(NICE) Norwegian Centre for Intelligent Computers and Electronics - NTNU. https://www.ntnu.edu/nice For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/294530/phd
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countries and exemptions from the requirements: https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8 Desirable experience (in ranked order): • Research in biosystematics (i.e
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conditions is an advantage. Applicants must be able to work independently and in a structured manner and demonstrate good collaborative skills. Applicants must have good written and oral English skills
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of the Center for integrative neuroplasticity (CINPLA) and in the INTED center. This PhD project will focus on reinforcement learning methods for generating complex structures with two possible application areas