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replacement in Eastern Asia, a key but understudied region in the ‘protein transition’. Focusing on a range of meat replacers, such as plant-based meat analogues, insects and lab-grown meat, the project focuses
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childbirth. Data from Norwegian and Swedish observational cohort studies (NOWAC, SCAPIS) and randomized clinical intervention trials in lactating women will be used. The position is based at the Department
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, techniques and the research basis for a portable AI-based, marker-free 3D modelling system to generate personalized avatars. We utilize recent advances in programming tools for hybrid physics-AI problems and
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transition’. Focusing on a range of meat replacers, such as plant-based meat analogues, insects and lab-grown meat, the project focuses on the entire region but zooms in on two key but highly different case
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build a CRISPR-based gene editing platform that can correct patient-specific mutations in ex vivo cell therapies for genetic immune diseases. We focus on correcting blood stem cells for curative therapy
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for mental health issues based on their genes and environment. The tools and data created will be shared to help other scientists study and address these important issues. The position(s) will be
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the University’ Centre for Global Sustainability, Institute of Health and Society and Department of History. They will be based in the interdisciplinary Global health politics research group at the University
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independently. Well-organised and able to structure own work. Ability to think creatively within a scientific framework. Employment in the position is based on a comprehensive assessment of all qualification
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Applications are invited for a fully funded PhD fellowship to be based at the Department of Psychology, University of Oslo. The position is linked to the project titled “An oxytocin intervention to support youth
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based on their individual risk profiles. Job description To contribute to the goal of the project, the researcher hired for the current position will be involved in multivariate data analysis of big data