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We looking for an independent and motivated post-doctoral researcher to conduct experimental and modelling work in a new project focusing on reducing negative impacts of climate change in
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networks are controlled, to develop predictive models of methane cycling in northern rivers. This postdoc position will focus on assessing how stream methane emissions are linked to permafrost thaw, using
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results into practical applications for end users. Subject Description The research aims to develop machine learning models for microbe detection, focusing on the mathematical foundations in geometry and
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different mixing and reactive properties compared to conventional fuels. In this project, turbulent mixing and combustion of hydrogen in air will be studied through optical experiments and numerical modelling
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spinal cord as a model system. You will engage a systematic strategy to identify these mechanisms by generating innovative mouse genetic strains, identifying embryonic defects and the underlying molecular
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of millions of lakes worldwide. The successful candidate will create innovative solutions that significantly enhance large-scale environmental simulations and meaningfully advance the modeling of global lake
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investigates inflammation in health and disease using cutting-edge exposure systems and advanced 2D and 3D cell models. In parallel, NanoSafety2 focuses on the toxicity assessment of particle emissions from
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meritorious if you have experience in: usability studies, user experience design. adaptability and personalization based on user models. Employment details The position is a temporary employment, for two years
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efforts. The theoretical activities at Chemical Physics focus on electronic structure calculations within the density functional theory together with mean-field kinetic modeling and kinetic Monte-Carlo
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relevant subject. Experience working with statistical data analyses and mixed models. Merit: Knowledge of forage crop management. Knowledge of statistical analyses of experiments, mixed models, and