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scenarios and strategies for its successful implementation. Using existing ICE-2 energy system models, you will address questions such as: How do installation and retrofitting times impact the restructuring
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problems. The mission of this consortium is to realize a new revenue model in the textile value chain, by scaling up and strengthening the (business/government/NGO) activities around sorting and recycling
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. In particular, the research project will focus on inferring trajectories from spatial transcriptomics data modelling at the same time the cells evolution in gene expression and in space. Required
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underpinnings of chronic pain and the dynamics of host-microbiome interactions in health and disease. Methodologically, we combine molecular biology, biochemistry, pharmacology, preclinical mouse models and the
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. The research school for stress response modelling in IceLab Starting in the spring of 2025, Umeå University’s interdisciplinary research hub, IceLab, will offer doctoral positions through the new Stress Response
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problems. The mission of this consortium is to realize a new revenue model in the textile value chain, by scaling up and strengthening the (business/government/NGO) activities around sorting and recycling
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Your Job: As part of an interdisciplinary team, you will develop approaches for the automated and large-scale provision and integration of energy systems data and models and apply data science
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according to an agreement. The application deadline is August 15th 2025. The research school for stress response modelling in IceLab Starting in the spring of 2025, Umeå University’s interdisciplinary
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; willingness to experiment with new data collection and model methodology development; motivation to cooperate in a diverse and multidisciplinary research team; excellent communication skills. Being fluent in
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the perspective of energy infrastructure. Using the existing energy system models of ICE-2, you will develop scenarios to analyze the effects on the German energy system and its robust design in a European context