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skills in coding for statistical and spatial analyses by relevant tools (e.g. R, QGIS and Python), as well as ability to manage large datasets of wall-to-wall environmental data. • Excellent oral and
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(most notably, distribution modelling); • Documented experience and skills in coding for statistical and spatial analyses by relevant tools (e.g. R, QGIS and Python), as well as ability to manage large
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focusing on rituals and/or measuring inter- and intragroup relations. Demonstrated expertise in survey design and analysis, including sampling, instrument development, implementation, and statistical
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portal (Norwegian). The selections made in the job application portal are used for anonymized statistics that all state employers include in their annual reports. More information about gender equality
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Professional qualifications (required) Relevant PhD degree (e.g. computer science, machine learning, statistics) Experience in developing deep learning models for 3D point cloud data Strong programming skills
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language skills Experience in the following will also count in the assessment of the applicants: computational and statistical methods for analysis; rodent behavioural assays, brain sectioning and
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. For more details about the requirements, please refer to the Employer portal (Norwegian). The selections made in the job application portal are used for anonymized statistics that all state employers
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institution for the duration of the fellowship. Experience with AI-related research and/or innovation is an advantage. A strong background in statistics is required, as well as experience in atmospheric
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background in statistics is required, as well as experience in atmospheric dynamics or climate dynamics, basic shell scripting, and python/Matlab/R or similar languages. Experience with “traditional” climate
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be employed by any other institution for the duration of the fellowship. Experience with AI-related research and/or innovation is an advantage. A strong background in statistics is required, as