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data. Develop and apply machine learning models to estimate uncertainty in climate impact statements. Analyse spatial and temporal patterns and trends in climate-extreme impacts. Cross-validate
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Data Science department can be found at https://scds.uoregon.edu/ds. Particular strengths of collaborative research at UO include astronomy, biomedical data science, climate science and modeling, cell
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, ultimately aiming to find better treatments for patients with cancer. This position is intended to provide experimental support by working in the laboratory of physician scientist Dr. Christine Eyler (https
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of observed meteorological elements at all spatial scales. ICV also constitutes an important source of uncertainty in climate model outputs, especially regarding the occurrence of climatic extremes. Furthermore
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comprising computational biologists, bioengineers, and immunologists. The candidate will have access to advanced platforms for single-cell and spatial omics, 3D tissue modeling, bioreactors, and in vivo models
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models or glioblastoma research Familiarity with transcriptomic methods (RNA-seq, FISH, spatial transcriptomics) Programming skills for data analysis (Python, R, or MATLAB) We offer Funding: Full position
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learning, AI, or statistical modeling applied to biological data Experience with genomics, transcriptomics, single-cell and/or spatial omics technologies Proficiency in scientific computing frameworks Strong
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project (www.bigdatpol.com ), we are looking for a doctoral researcher with a strong interest in AI-driven analysis, modelling and decision support. About the project Crime and security constitute a
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can be inhibited, leading to a form of topological delocalization. This phenomenon has never been experimentally tested. The proposed internship will contribute to the preliminary design and modeling
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
the surface properties of the Asal-Ghoubbet rift by massive inversion of the Hapke model on Pleiades multiangular images. Remote Sensing of Environment 322, 114691. https://doi.org/10.1016/j.rse