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microenvironment, and other biological processes. Conduct preclinical studies using in vivo disease models (cancer, inflammation, organ injury, etc.) and new alternative methodologies (advanced biological models
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translational medicine using a "bench-to-bedside" approach. By harmonising and analysing diverse biomedical data, while focusing on the secure data processing and predictive modelling, we aim to drive progress in
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the conditions of crop, pasture, and their environment with advanced remote sensing and geospatial technologies; Develops and refines algorithms and workflows for crop and pasture monitoring, modeling, prediction
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, biophysical assays, and murine models of pulmonary embolism. A second goal will consist of integrating experimental findings with in-silico models and microfluidic flow systems to explore the interplay between
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the context of critical illness. This position focuses on computational modeling of host-response mechanisms using high-dimensional multi-omics datasets. The fellow develops novel computational pipelines
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advanced data analytics and quantitative models to challenges in nutrition and health? This position at Fraunhofer-Chalmers Research Centre offers the opportunity to work as a Senior Applied Researcher in
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the frame of the FNR-CORE supported project OPTMONITOR (Optimal Monitoring and Coupled Modeling for Climate-Driven Landslide Risk Detection) at the University of Luxembourg (Faculty of Science, Technology and
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backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services
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preparation, development and verification of models and generalization of solutions. Your background For this position, you are required to have a PhD in electronics, metrology, computer engineering or a
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topics in international macroeconomics and finance Responsibilities • Conduct empirical analysis • Review and summarize academic literature • Assistant in theoretical and computational modeling • Prepare