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responsible for adapting existing mathematical and statistical methods for analysis of high-dimensional imaging data, and analysing quantitative imaging data from a variety of sources, including Spatial
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essential that you hold a PhD/DPhil (or close to completion) in mathematics, computational biology, data science, statistics, physics, or a related discipline, and have experience of analysing and
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cloud data and 2D floor plans to assess spatial and visual properties of EDs, ensuring data accuracy through ground-truthing. Apply cluster analysis and statistical methods to classify EDs into spatial
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of pedology and/or hydrology is a plus - Strong skills in ecological data statistical analysis Specific Requirements PhD degree of less than 3 years. LanguagesENGLISHLevelGood LanguagesFRENCHLevelGood
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Qualifications: We seek exceptionally strong candidates with a PhD in statistics, biostatistics, computer science or a related field. Candidates with demonstrated accomplishment in academic research, as can be
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cancer progression, immune evasion, and therapeutic resistance. We place a strong emphasis on the use of spatial biological approaches applied to human tumour models including organ/tumour perfusion, slice
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imagery). Experience in building data models using Python or other statistical and/or mathematical programming packages. Proficiency in developing machine learning algorithms to analyze spatial-temporal
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further including to automated platforms to generate large statistical data sets. We will also experiment with untried higher spatial resolution techniques. The large, multi-dimensional data sets will be
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Oldenburg Oldenburg, Niedersachsen | Germany | 3 days ago
of Oldenburg Your Profile PhD in marine ecology, finalized by the start of the project Advanced statistical modeling skills including analysis of biodiversity time series and functional traits, evidenced by
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applicants will have:*Expertise conducting spatial and statistical analyses*Experience with scientific computer programming in R and Python*Formal training or experience applying quantitative and spatial