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Postdoctoral Research Associate who will focus on creating innovative artificial intelligence algorithms for the trusted visualization of large-scale 3D scientific data. This position resides in the Data
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Description Overview: We are seeking a Postdoctoral Research Associate who will focus on creating innovative uncertainty quantification and visualization algorithms that enable trusted visual representation and
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National Aeronautics and Space Administration (NASA) | New York City, New York | United States | about 1 month ago
transfer algorithms for NASA GISS‘s general circulation model (GCM) to study radiative interaction and feedbacks between various atmospheric constituents and the climate system. Potential specific topics
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testing of model-free algorithms for real-time optimization of turbine operating conditions (e.g., yaw set points). Other projects may be assigned by the supervisor depending on skills and technical needs
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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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by integrating large-scale single-cell foundation models with structured biological knowledge encoded in genomic graphs. The project will also deliver efficient algorithms to train these models under
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-terrestrial networks, and the performance evaluation of these solutions in challenging IoT scenarios. The position involves both theoretical and experimental research, including algorithm design, simulation
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9 Feb 2026 Job Information Organisation/Company CNRS Department Sciences et Ingénierie, Matériaux, Procédés Research Field Computer science Mathematics » Algorithms Researcher Profile First Stage
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properties of macromolecules, developing novel ways to combine quantum chemical methods and machine learning, developing quantum algorithms for computational chemistry on quantum computers, and applying
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datasets (e.g., RNA-Seq, epigenetics, cancer genomics, or metabolomics). Statistical Knowledge: Strong understanding of algorithmic, statistical, and ontological concepts in biology. Communication: Excellent