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Field
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on soil organic matter cycling Literature research and (meta-)analysis to provide evidence-based knowledge for model parameterization Quantify the coupled carbon and energy turnover of specific biomolecules
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for generating ultra-short and ultra-broadband laser pulses for field-resolved infrared spectroscopy Setup of a novel, enhancement-cavity-based spectrometer for the analysis of medically relevant gases What you
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at varying PBF-LB fabrication process parameters (at Uppsala University), collect experimental data on microstructure, mechanical and corrosion properties; ii) determine, using sensitivity analysis, impact of
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of microfluidic cultivation platforms for co-cultures Live-cell microscopy (including fluorescence, phase contrast and time-lapse) for the analysis of cell interactions. Conducting cultivation experiments with
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and Marine Research. The tasks include: scientific advancing methods of satellite altimetry analysis over the Antarctic Ice Sheet analysis of measured surface elevation changes in conjunction with
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reuse of energy systems analysis processes. In line with FAIR and Linked Open Data principles, you will design interfaces that enable the smooth processing of big data in the context of scientific, AI
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or equivalent) in geodesy or a related subject (geophysics, geoinformatics, physics, mathematics) sound experience in applying geodetic space techniques, especially in the analysis of geodetic GNSS measurements
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experimental molecular biology and data analysis. Doctoral candidates can specialize in genomic and molecular biology techniques, as well as in algorithms, statistics, and artificial intelligence for molecular
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Degree Doctor of natural sciences (Dr rer nat) Doctoral degree or degree awarded by University of Bonn Course location Bonn In cooperation with Bonn International Graduate School of Mathematics
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: A completed university degree (Master or equivalent) in computer science, data science, applied mathematics, physics, materials science, or a related field Prior experience in computer vision, deep