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Your Job: You will develop instrumental analytical and theoretical methods to determine the origin of hydrogen and, in particular hydrogen carriers (including methanol, LOHC systems, formic acid) by
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As part of the German government's artificial intelligence (AI) strategy, the successful Saxon competence center ScaDS.AI Dresden/Leipzig (Center for Scalable Data Analytics and Artificial
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formation under conditions as natural as possible along the gradient. We will measure 13CO2 fluxes in the field and combine these data with the incorporation of the 13C tracer into different SOM fractions
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data handling Strong self-initiative and willingness to learn and to quickly gain an understanding of new subject areas Joy in working independently, as well as within a team Strong problem-solving
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such as the NEPS. Potential research areas include (but are not limited to): Item response modeling of achievement tests Analysis of process data (e.g., response times) to enhance competence measurements
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experience and enthusiasm for experimental work Basic knowledge of instrumental and preparative chromatography Fluent in written and spoken English Confident handling of common analytical software (e.g. Excel
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) Optimization and tuning of catalyst layer performance and durability: morphology, hydrophobicity, porosity Product analysis and analytical chemistry; investigation of side reactions System process analysis and
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Topic: The rapid advancement of digital health technologies presents unprecedented global opportunities and challenges in public health and healthcare, data management and analytics in prevention
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analytical chemistry, mass spectrometry, or trace gas measurements is an asset Enthusiasm for laboratory and field work Willingness to engage in programming and data analysis (preferably Python) Excellent
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and data analytics (including machine learning and deep learning); from high-performance computing to high-performance analytics; from data integration to data-related topics such as uncertainty