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modeling of polymeric, reinforced, and porous materials, with strong expertise in large deformations and numerical homogenization. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR7649-JULDIA
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experience in the processing and integration of massive datasets (‘big data’), they will contribute to ecological modelling, environmental impact forecasting, and soil biodiversity analysis in the central
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in data integration, model design, and large-scale training by combining multi-modal scientific data, knowledge graphs, physics-aware machine learning, and GPU/HPC computing to develop transparent and
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post-operative animal care including documentation; 2) assisting with all large animal procedures, 3) record keeping, data acquisition, and sample collection and processing during large animal surgery; 4
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developed to transfer information from the pangenome variation panel to large mapping populations through imputation so that association testing between complex traits and SVs will eventually be possible
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. Please check our website (www.ec2-big-nse.de ). Submit application to https://www.ec2-big-nse.de Accommodation The BIG-NSE administration office supports students in their search for suitable accommodation
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or equivalent Skills/Qualifications Interés en el desarrollo de aplicaciones y servicios de procesado de datos, big data y soberanía de los datos. Experiencia en interfaces para gestión de espacios de datos
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description This research focuses on developing and validating Big Data-driven methods
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Studierendenwerk Bonn (further information: https://www.studierendenwerk-bonn.de/en/accommodation/ ). For more information on housing in Bonn, please visit our website: www.uni-bonn.de/en/university/university-life
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, graphs); experience with analysis and processing of large volumes of data; development of reproducible scientific software; proficiency in Python and libraries (Pandas/NumPy and PyTorch/TensorFlow/Scikit