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Field
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mammalian cell lines and primary cell cultures. Perform confocal imaging and data interpretation. Analyze experimental data using statistical software and prepare research reports. Manage laboratory resources
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-on experience with biological data ● Strong Python skills and experience with PyTorch or JAX, together with the statistical grounding to reason about the models you use ● A GitHub account with code you have
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, (lab) experiment, data donation), ideally already demonstrated in your thesis or other research projects you were involved in; experience with various techniques of quantitative statistical data analysis
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of the graduate school PE&RC (https://www.pe-rc.nl/ ) through which you can follow courses on ecological subjects, research methods, statistical analyses, and transferrable skills. Terms of employment
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degree (completed or near completion) in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related quantitative field. A solid background in machine learning, statistics and/or
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various techniques of quantitative statistical data analysis, experience with longitudinal analyses is a plus; experience with, or knowledge of, focus groups and analysis of qualitative data; an excellent
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this additional qualification.-You have strong skills in statistical, econometric and quantitative data analysis and have experience with statistical software packages; furthermore, you are keen to develop
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Applications are invited for a Research Assistant - Statistical Geneticist to join the Genomics and Bioinformatics Core (GBC) within the Institute of Metabolic Science - Metabolic Research
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 1 month ago
. You will have the freedom to ask what information is contained in these data and develop the computational and statistical approaches needed to extract it. Working closely with experts in imaging
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)medical or nutritional sciences.Preferably you have experience with working with large datasets in statistical software packages such as R, Python or SPSS. Proficiency in English at C1 level or higher (CEFR