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omics platforms (e.g., fluorescence microscopy, mass spectrometry imaging (MSI), Raman systems) and will develop computational and statistical data analysis methods to improve data quality, information
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analysis of sequence and genome data (bioinformatics). Experience working with non-model organisms (animals), ideally marine invertebrates. Oral and written communication skills in English. Desirable skills
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Strong interest in vegetation and ecosystems dynamics, biodiversity and climate change and human-nature interactions, and in interdisciplinary collaboration Very good skills in data analysis and
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practical experience with Linux/Unix, High Performance Computing, and scientific programming is recommended or the willingness to learn these skills basic expertise with scientific data analysis good skills
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(preparation and staining (IF, IHC), confocal and fluorescence microscopy, analysis and evaluation) Experience with quantitative analysis of imaging or physiological data (e.g., microscopy, cardiac imaging
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mathematical experts at RICAM with the goal to investigate influence of variable root growth coordinate with UZH and RICAM documentation of data, analysis scripts and model code, and organize knowledge transfer
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application. Information on the protection of your personal data can be found at https://leibniz-ifl.de/en/functions/data-protection-job-advertisement The IfL advocates professional equality for all genders
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, molecular genetics and genomics. You are experienced with Next Generation Sequencing methods. Ideally you have an affinity to command-line based bioinformatic data analysis. Experience with R and Linux in a
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to improve the clinical care of inpatients in Southeast Asia and Africa Preparation and analysis of scientific data Writing scientific texts and publications Design and coordination of field activities in
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world with increasing digitalization and medical needs. Our research integrates materials chemistry, biological processes, physical analysis, process engineering and data science. We collaborate with