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collaboration with survey providers in Denmark and Germany. Analyzing survey data using quantitative methods such as conjoint analysis, regression modeling, and causal inference techniques. Writing academic
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electrolyte and water reabsorption. The postdoc will be expected to explore the potential of modulating bile acid signaling in cell and mouse models and perform metabolomic and transcriptomic analyses
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mathematical ability Experience with symmetry analysis, group theory, or topological band theory Demonstrated experience in programming and contributions to open-source software Excellent communication skills
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the biogeochemical mechanisms that underpin the resilience of restored wetlands, integrating field observations, laboratory experiments, and modelling approaches. You will explore how nutrient dynamics, hydrological
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the biogeochemical mechanisms that underpin the resilience of restored wetlands, integrating field observations, laboratory experiments, and modelling approaches. You will explore how nutrient dynamics, hydrological
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in vivo models to investigate drug responses in relation to immune-cell mediated killing of multiple myeloma cancer cells. Your job responsibilities As Postdoc in Cancer immunology/multiple myeloma
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Postdoc in development and testing of electrodes for liquid alkaline water electrolysis - DTU Energy
multi-physics modelling, autonomous materials discovery, materials processing, and structural analyses. We also focus on educating engineering students at all levels, ranging from BSc, MSc, PhD
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chemical–biological pathway. The advertised positions will support these efforts through research on advanced carbon capture methods, process modelling and optimization, and biological CO2 valorization in
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-based simulation model for assessing future mobility technologies in the Greater Copenhagen region. Explore the development of machine-learning based scenario discovery for future mobility policy design
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candidate will develop and test novel user interfaces that integrate state-of-the-art Large Language Models (LLMs) with novel logic-based multi-robot planning algorithms. This work will be evaluated through