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. The project’s PI is Associate Professor Iselin Åsedotter Strønen. For more information about the project, see https://www4.uib.no/en/research/research-projects/invisible-women-of-the-sea-gendering-fishery
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to work structured and handle a heavy workload having a good command of both oral and written English Requirements for competence in English A good proficiency in English is required for anyone attending
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to evaluate and inform digital health interventions for women at increased risk of GDM. The project will primarily utilize data collected from a completed randomized controlled trial (https://bump2babyandme.org
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Fund. automatic membership in the Norwegian Public Service Pension Fund , which provides favourable insurance- and retirement benefits favourable membership terms at a gym and at the company sports club
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to evaluate and inform digital health interventions for women at increased risk of GDM. The project will primarily utilize data collected from a completed randomized controlled trial (https://bump2babyandme.org
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, at Makerere University, Uganda and University of Cape Town, South Africa). More information about the network can be found here . The PhD fellows will automatically be admitted to the Faculty of Social Sciences
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the University of Oslo. Place of work is IFI (the Department of Informatics) / PT (Programming Technology), at Blindern, Oslo. Job description Automatic human activity detection (HAR), mainly transport
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University, Uganda and University of Cape Town, South Africa). More information about the network can be found here . The PhD fellows will automatically be admitted to the Faculty of Social Sciences' PhD
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. The position and associated tasks must be carried out in accordance with the applicable laws and regulations for government employees, including also the Act on Control of the Export of Strategic Goods, Services
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., deep learning methods, multimodal AI) for the automatic identification of behavioral cues during ecological interactions with people and the environment and analyses of video and speech/language data