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sensor data, with applications in disease modeling and the development of material science-based innovations. These efforts aim to optimize system performance and uncover novel biological insights in close
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soon as possible. The position is within the Math+ project "Anisotropic microfluids -- fluctuations, control, effective models and their numerics “. Here, we study anisotropic microfluids and the effect
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for the Quantification of Domain Uncertainty Propagation in Cardiovascular Models" as part of the Berlin Mathematics Research Center MATH+. The purpose of this position is to conduct research in the field of model
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with data-based models and numerical dynamo simulations. The successful candidate will contribute to studies of time-averaged geomagnetic field morphologies and core dynamics during transitional events
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after damage. Methodologically, the project aims to develop novel organoid-on-a-chip models of kidney injury. The applied techniques will include mouse and human kidney organoids, tissue engineering
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creative solutions for complex chemical and process engineering problem. Dehydrogenation processes: Construction of a test stand for the dehydrogenation of diol-based carrier molecules Explorative research
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Oldenburg Oldenburg, Niedersachsen | Germany | about 1 month ago
of Oldenburg Your Profile PhD in marine ecology, finalized by the start of the project Advanced statistical modeling skills including analysis of biodiversity time series and functional traits, evidenced by
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assigned to the research project "Randomization of Surrogates for the Quantification of Domain Uncertainty Propagation in Cardiovascular Models" as part of the Berlin Mathematics Research Center MATH+. The
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—for bacterial control and therapeutic application. Together, we identify functional prophage genes, develop genetic tools, and test engineered phages in infection models. Your tasks Plan and perform in vitro and
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. Job description: - first-principle modeling and simulations of electrolytes - development of new machine learning strategies and quantum simulation approaches - application of specially developed