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Field
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audiences and collaborate across disciplines; proficiency in spoken and written English. Experience with plant pathogens, microbiome sequencing, image-based phenotyping, R/Python, statistics or machine
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apply advanced statistical and computational methods to analyze genetic data generated from simulations, outputs from biophysical models, or empirical genomic data to answer questions in spatial
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of the Division of Agricultural, Food and Resource Economics. You have experience with or are eager to work with large databases and database management software. You have starter skills in statistical, econometric
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such as Remark). o Work with other lead researchers to produce clean survey datasets across all modes, conduct statistical analysis, and produce data summary files and reports and other deliverable
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to accurate sample reconstructions using advanced signal processing and tomographic reconstruction algorithms. With the inclusion of noise the object estimation accuracy will be based on statistical concepts
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qualifications: Knowledge of polymer processing and statistical experimental design (DoE) Collaborative mindset and enthusiasm for working in interdisciplinary teams Strong organizational skills and a structured
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collective behaviour Statistical and computational physics for complex data Astrophysical and space plasmas Space environment, space weather and technological impacts Magnetic confinement fusion energy Sea ice
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Master’s degree in physics, applied mathematics, or related disciplines. You have knowledge in soft matter/complex systems physics, biological physics, or statistical physics. You enjoy working in
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 2 months ago
and advance statistical, image analysis, and machine learning approaches Develop interpretable models that reveal biologically testable relationships and generate new scientific hypotheses Independently
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of the position; a solid foundation in quantitative research methods and statistics, and a strong interest in multilevel modelling; excellent written and spoken English; the ability to work independently, manage a