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9 Mar 2026 Job Information Organisation/Company Université Paris Cité Department Center for Research in Epidemiology and Statistics (CRESS) Research Field Medical sciences » Epidemiology Biological
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interdisciplinary, and together we contribute to science and society. Your role We seek a highly motivated AI scientist, biostatistician or computational biologist who is well versed in the statistical and machine
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be successful, you will have: MSc in Physics, Mathematics, Engineering, Computer Science, Statistics or related disciplines with a strong background in mathematical modeling, algorithms and
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at international conferences Where to apply Website https://www.academictransfer.com/en/jobs/359893/phd-position-individual-behavio… Requirements Specific Requirements you have an MSc degree in (behavioural
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., PsychoPy, E-Prime, Gorilla, Presentation). Hands-on experience in data visualization, data analysis, and programming in R and/or Python. Experience in, and aptitude for, complex statistical modelling (inc
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, particularly those related to reproduction and meiosis. To this end, a new cattle pangenome that includes near complete assemblies of the sex chromosomes will be generated and statistical methods will be
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The Quantitative Genetics research group is interested in developing statistical genomics toolboxes to decipher the genetic architecture of important crop traits, such as grain yield, adaptation
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_______________________________________________________________ Requirements MSc degree (or equivalent) in soil science, ecology, environmental science, or a related field Laboratory experience Good command of English (sufficient for scientific literature and communication
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Degree Dr rer pol (PhD) with integrated MSc in Economics (specialisation economic research) Course location Bonn Teaching language English Languages All courses are taught in English. Full-time
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the dynamical and statistical characteristics of the numerical model data. The candidate shall explore whether the above data assimilation can be done in one step for full 3D fields, or if it is advantageous