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-B4 Investigators: Prof. Dr. Meng Wang, Chair of Traffic Process Automation , and co-supervised by another expert in traffic control Requirements: excellent or very good university degree
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, these models often use simplified, linearized assumptions, limiting their capacity to capture the nonlinear complexities inherent in real-world hydrological processes. Recently, there has also been the branch
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or functions (e.g., by phages) – to optimize microbiome composition and function Improvement of our current tool for microbiome modelling Your profile Masters, Diploma or equivalent degree in Bioinformatics
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equivalent) in computer science, data science, applied mathematics, physics, materials science, or a related field Prior experience in computer vision, deep learning, or signal processing; familiarity with
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actions and optimized lifecycle management of CI assets. Objectives DC4 will develop an integrated BIM-SHM framework for real-time structural performance monitoring and dynamic visualization in critical
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for climate-positive and CO2-negative processes. What you will do Optimization of the pilot plant for the combustion of solid fuels (biomass, waste) with oxygen and subsequent CO2 capture Development of models
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master's degree in agricultural or environmental economics, applied mathematics, or a related field Good background in bio-economic modelling, CGE modelling, and optimization techniques Experience with
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processes that produce energy and raw materials. The Department of Reactive Transport is looking for a PhD Student (f/m/d) Tomography of desorption reactions: positron emission tomography for quantifying
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and develops a wide range of topics related to chemical hydrogen storage along the entire process chain. We place a particular emphasis on LOHC technology, addressing issues across different scales. Our
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modeling, optimization, and/or data analytics. Description of the PhD topic (subproject C1 - New metrics for transportation system appraisal): Transportation systems must deliver “function” (i.e