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Field
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biochemical techniques to study details of antigen recognition and effector functions of autoantibodies Engage in data analysis and collaborate with computational scientists. Your qualifications: MSc
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for improved understanding of structural and kinetic processes in electrolytes; and machine learning concepts for improved analysis of experimental and simulated data. Material Synthesis Within this research
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of experiments within the framework of the scientific project plan Develop and establish new methods in the laboratory to enable new research approaches Isolation of primary cardiomyocytes and analysis
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for data analysis and experiment automation (Python preferred) Excellent English communication skills (written and verbal) Demonstrated ability to work in interdisciplinary and collaborative environments
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of functional and phenotypic assays. Findings from these studies will be validated in vivo and incorporated into an integrated analysis framework relating the experimental data back to clinical
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networks and machine learning strategies for the analysis of scattering data. Large amount of scattering data obtained in our group requires development of the advanced analysis techniques. In this project
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. - Neural networks and machine learning strategies for the analysis of scattering data. Large amount of scattering data obtained in our group requires development of the advanced analysis techniques. In
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chemistry, biophysical analysis via optical spectroscopy as well as the detection of nucleic acid in homogenous solution and in situ. The project also involves fluorescence microscopy and flow cytometry and
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, data collection, and data analysis as outlined in the research plan and collaborate with others. Collaborate with biostatisticians or data analysts, if required, to interpret and analyze complex data
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groups of Guinea baboons that are part of a community of more than 400 individuals. We combine behavioral observations, analysis of ranging patterns using GPS data, population genetics, acoustic analyses