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, starting 01.06.2026, ending 31.05.2030): Postdoc position (f/m/d) in the department “Competencies, Personality, Learning Environments” (Focus: socio-emotional and cognitive competencies) The Leibniz
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research associates to develop and apply theoretical and computational approaches to study complex cell biological systems. The emphasis will be on combining statistical inferences and biophysical modeling
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Description The postdoc will plan and conduct brain imaging studies on cue-reactivity, craving, and impulsivity in eating disorders, in the context of an IReSP funded research project. The postdoc will analyze
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 22 days ago
science, or a related field Strong background in signal processing, data analysis, and statistical modeling Programming skills in Python and experience with reproducible workflows Experience working with
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groups. Postdoc position responsibilities will include: Analyzing longitudinally collected virological and serological data on zoonotic bat viruses Experience with environmental data and/or movement data
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in iPSC-derived cellular models. The position is ideal for someone hoping to be involved in grant-funded research as well as increase their publication record during postdoc and launch an independent
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program more than 260 PhD students and 200 postdocs will be part of the Research School. The DDLS program has four strategic research areas: cell and molecular biology, evolution and biodiversity, precision
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, PRS, pathway analysis, or Mendelian randomization) and statistical analyses in R or Python; the candidate must have programming skills, ability to handle large datasets, experience in scientific
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, to perform data analysis derived from diverse scientific topics in collaboration with PhD students and postdocs, to train students and postdocs in basic data analysis pipeline implementation and bioinformatics
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the following areas: Air and surface sampling of fungi in buildings and on materials Basic statistical analysis knowledge (R or similar) and multivariate statistical methods Cross-disciplinary research