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intelligent transportation systems (ITS), with an emphasis on developing and deploying state-of-the-art Large-Language Models (LLMs), Vision-Language Models (VLMs), and Vision-Language-Action (VLA) models
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, to create a responsible and innovative university to serve as a model for the 21st century. Within ICN, the ChemSenSim group (https://lab.chemsensim.fr/ ) develops interdisciplinary research projects
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Design, develop, and implement advanced algorithms, models, and software tools for spatial data analysis, machine learning, and AI-driven geospatial applications Lead and collaborate on interdisciplinary
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Sapere Aude – dare to know – is our motto. Our students and employees develop important knowledge that enrich both the individual and the community. Our academic environment is characterised by
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developed countries, smartphone penetration exceeds 80%. The automatic transport mode detection (TMD), when effectively exploited, possibly using some kind of machine learning algorithm, provides more
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 2 months ago
include (but are not limited to): Develop algorithms to characterize aerosol speciation from LIDAR fluorescence signals Develop machine learning emulators to represent forward operators for polarimeter-only
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Computing Applications group in CSD has an immediate opening for a Postdoctoral Research Associate to design, develop, and deploy machine-learning and high-performance computing workflows, algorithms, and
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for at least 6 months. During the contract – no other salary from NCN-funded projects and no other employment contract. Experience in data processing, designing or developing computational algorithms
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will be focused primarily on the development and application of novel computational algorithms to analyze and integrate diverse omics datasets, including single-cell RNA-seq, spatial transcriptomics and
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databases of more than 1 million records and nationwide hospital data sets for use in health services research and quality analyses. Create analytic files. Develop the standard statistical algorithms