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to develop a biogeodynamic model, by coupling a trait-based eco-evolutionary model (e.g. AdaScape) into a reduced-complexity river delta model (e.g. DeltaRCM). We will use the model to synthesise information
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, ocean, marine ecosystem, and impact models of different complexity and will include both traditional and new ocean modelling approaches with the final objective of delivering: (i) coordinated and
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performing simulations with computational models of the Earth system on different levels of complexity scientific publication records appropriate for the experience level experience in scientific software
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levels of the brain – from molecular and cellular processes to complex neuronal networks and behavior. The LIN is a foundation under public law and committed to a comprehensive policy of Equal
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the Research Group “ Numerical Mathematics and Scientific Computing“ (Head: Prof. Dr. V. John) starting September 1, 2025. The position is assigned to the research project "Randomization of Surrogates
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Identification of soil invertebrates (e.g. mites, springtails, insects) using modern and classical techniques Laboratory analyses of soil properties Statistical analysis of complex ecological datasets Presentation
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networks of functional gene and protein regulation (https://www.ipb-halle.de ). The position is located in the department BPI (Biochemistry of Plant Interactions) and the Program Center for Plant
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output of the neutral atmosphere dynamics and chemistry of UA-ICON. A requirement will be to install TIE- GCM at the supercomputer of the German Climate Computing Centre, where UA-ICON is running
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for multimodal inferences, combining computer-vision, environmental parameter measures and DNA data. Your role will be central in data acquisition and foremost machine-learning models creation. You will
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master's or diploma degree in computer science or mathematics already successfully completed doctorate confident demeanor and proficient use of German and English (both equivalent to at least B2) expertise