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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | about 3 hours ago
Job Code: 21-24 Job Offer from June 10, 2024 The Max Planck Institute for Multidisciplinary Sciences in Göttingen is a leading international research institute of exceptional scientific breadth
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PhD on Motives for Statistical Reporting Practices (1.0 FTE) (V24.0329) « Back to the overview Job description Statistical results of empirical studies in the behavioral and social sciences have
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, integrated, embodied systems, you will co-create, validate, and disseminate a statistical Index of Community Assets (IoCA) to capture aspects of community and belonging in neighbourhoods that are not well
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primary analysis to apply bioinformatics solutions to biomedical problems. You will be responsible for carrying out data processing and integration, statistical analysis, presentation and interpretation
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. Qualifications Applicants should hold a PhD degree in in environmental engineering, environmental chemistry, biotechnology, chemical engineering, data science, statistics, mathematics or equivalent. Experience in
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). The institute also maintains locations in Dedelow and Paulinenaue. The in-house project CRoP-SMART (Comprehensive Research on Crop Performance: Statistical Methods for Agricultural Research and Technology) will
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PhD in mathematics, physics, bioinformatics or statistics, or a related subject area with strong element of mathematical modelling. They will also have a First-class degree in any area of science
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to the Senior Director of Statistics to plan support for assigned studies and submissions. Participate in research on statistical methodology and its applications pertinent to Pfizer's business needs. MINIMUM
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statistics • Collaborate with colleagues from other disciplines within the university • Develop grant-funded research projects • Supervise MSc students, PhD students and postdoctoral researchers
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Job Description The SRF is expected to: 1. Conduct independent and lead high quality research in the fields of Bayesian optimization, Simulation optimization, and simulation modeling