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-France 75 005, France [map ] Subject Areas: Machine Learning Statistical Physics Appl Deadline: 2026/01/15 11:59PM (posted 2025/11/04, listed until 2026/05/04) Position Description: Apply Position
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. The PhD will combine behavioural experiments, machine learning, and explainable-AI methods to answer questions: Do SR techniques improve human face identification accuracy? How do SR-enhanced images affect
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or willingness to learn quickly. Publications, thesis work, or demonstrable projects in computer vision, multi-modal ML, digital twins or biomedical ML. Familiarity with uncertainty quantification and model
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team (https://research.pasteur.fr/en/team/machine-learning-for-integrative - genomics/) at Institut Pasteur, led by Laura Cantini, works at the interface of machine learning and biology (tools developed
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 10 hours ago
to constrain the representation of aerosols in the NASA GEOS Earth System Model. Activities that would be involved in this project include (but are not limited to): Implement machine learning transfer learning
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for the Advancement of Surgery) initiative. The Research Associate will be responsible for developing machine learning algorithms and creating predictive models. The ideal candidate must demonstrate a robust background
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models (e.g., YOLO, U-Net, EfficientNet, ResNet, FPN, Fast R-CNN) Computer vision techniques and algorithms Python and relevant libraries (e.g., PyQt, OpenCV, NumPy, scikit-learn), particularly
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adaptation, synthetic data generation, and cross-modal learning to enable models that generalize across defect types and machine configurations. This ensures scalable, accurate defect detection even in low
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machine learning (ML) models and optimization algorithms specifically designed for highly dynamic satellite communication (SatCom) systems that can handle networks of varying sizes and configurations
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developing innovative solutions for integrating geophysical data and machine learning approaches for geological modelling and site characterization. The position is expected to perform independent and