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spectroscopic parameters, with a particular emphasis on magnetic resonance. This is an ideal opportunity for candidates interested in applied quantum chemistry, especially with a focus on heavy element compounds
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and cellular analysis of the ischemic brain using spatial and single-cell transcriptomics Profile of the graduate The graduate understands key areas of informatics, such as algorithms and software
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applications of advanced spatial data analysis methods, data collection, and interpretation of remote sensing data, database system theory, mapping, spatial data distribution, development of new cartographic
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similar sites around the world. Requirements: A master's degree in microbiology or a related field Basic training in microbiology (preferably environmental microbiology), statistical analysis and
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for this programme Detailed information about the study programme Offer of dissertation topics: DSPII:Personalized medicine and its approach based on the analysis of immune system–microbiota interactions as a tool
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of the dissertation topics: 15. 11. 2025 Application by: 15. 12. 2025 Apply for this programme Detailed information about the study programme Offer of dissertation topics: Analysis of metabolic dependencies in acute
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, interplay between delta subunit and sigma factors, interactions of a recently discovered transcription factor MoaB2 with mycobacterial sigma factors and RNA polymerases. Cryo-electron microscopy will be used
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or accepted). Experience with morphometric analysis, climatic niche modelling and/or significant fieldwork experience in tropical mountains is advantageous. Benefits: 5 weeks of paid holiday yearly, subsidized
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or similar tools for data analysis is beneficial. · The working environment is international; excellent communication skills in English are essential. Position Details · Funding: Fully funded PhD (4 years
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Previous experience in soil organic matter dynamics and stability and/or related to soil fauna Previous experience in statistical analysis of data, preferably in R Previous experience in biomarker extraction