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experience growing, managing, and phenotyping plants in the field and greenhouse. You have experience using modern approaches in root phenotyping, image analysis, or simulation modeling to understand
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innovative machine learning architectures for the mining, prediction, and design of enzymes. Combine state-of-the-art ML (e.g., deep learning, generative models) with computational biochemistry tools
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: Develop innovative machine learning architectures for the mining, prediction, and design of enzymes. Combine state-of-the-art ML (e.g., deep learning, generative models) with computational biochemistry
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recent work has uncovered that consumption of a western diet can drive lipid changes that activate microglia, causing neuroinflammation. Using a series of animal models of dementia, murine cell culture
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transformation." The project will investigate the relationship between road safety and safety culture. A theory-based model of road safety culture will be developed and validated through surveys in various
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quantification, model-order reduction, or multi-fidelity methods. The primary fields of application are life science, medicine and health, earth observation and robotics. Consequently, a MUDS student will learn
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Max-Planck-Institut für Kohlenforschung, Mülheim an der Ruhr | M lheim an der Ruhr, Nordrhein Westfalen | Germany | 2 months ago
the University Duisburg-Essen), the candidate will study structure changes associated with complex activation processes of zeolites combined with their adsorption properties. Structure evolution will be
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the comprehensive field of Earth System Modelling, with emphasis on the interactions between the natural and the human systems. The scientific subject is the development, application and evaluation of a hierarchy of
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features with an emphasis on vegetation complexity, urban infrastructure, and bird diversity. The thesis is part of a greater project studying urban green space and soundscapes and how these relate to human
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to probe metabolic states and function of control mechanisms. Analysis of strain performance and control mechanisms using computational tools (e.g., flux balance analysis, kinetic models, network component