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sustainable fluorination reactions. Under the supervision of Dr. Chris Ewels, a CNRS Research Director and expert in DFT modeling of nanocarbon materials, the postdoc will lead Work Package 2 (WP2), which aims
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, including direct knowledge of its Julia-based modeling environment, software architecture, domain-specific modules, and underlying computational infrastructure. ● Prior hands-on experience contributing
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Mobasher. It involves a diverse range of activities including: structural and geotechnical modeling, machine-learning model development, structural sensing and health monitoring, conducting physical
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Infrastructure? No Offer Description The selected candidate will lead the metabolic modeling efforts within our Biotechnology pillar. The primary goal is to use computational modeling and network analysis
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. Knowledge, Skills, Abilities: Demonstrated ability to independently prepare technical reports, graphics and manuscripts. Rodent-related knowledge, including animal model development and maintenance, rodent
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with cardiovascular or fetal imaging data. • Knowledge of machine learning model development, validation, and clinical translation. • Experience working with DICOM data, PACS systems, and 3D
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mathematical experts at RICAM with the goal to investigate influence of variable root growth coordinate with UZH and RICAM documentation of data, analysis scripts and model code, and organize knowledge transfer
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postdoc to study how supply chains can stay resilient and meet regulatory demands, using system modeling and scenario analysis. Job description Supply chains are increasingly exposed to complex and
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10 Apr 2026 Job Information Organisation/Company CNRS Department INSERM U960 - LABORATOIRE DE NEUROSCIENCES COGNITIVES Research Field Neurosciences Psychological sciences » Cognitive science
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motivated to advance trustworthy artificial intelligence in medical imaging? In this postdoctoral position, you will work on explainable AI and foundation models for CT imaging, combining methodological