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and image analysis within the project, responsible for designing and iterating on machine learning architectures, managing training pipelines and datasets, and optimizing models for deployment across
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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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et d'assurer la stabilité des performances dans le temps. Cette thèse s'inscrit dans le cadre de l'apprentissage continu, un domaine émergent du machine learning, qui vise à concevoir des modèles
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 8 days ago
., Data-driven Flower Petal Modeling with Botany Priors, CVPR 2014. 2. Q. Zheng et al., 4D Reconstruction of Blooming Flowers, CGF 2017. 3. S. Ghrer et al., Learning to Infer Parameterized Representations
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will produce a dataset on social interactions aimed at training machine learning models for human-robot interactions. Robot decision using internal simulations : As mentioned at the beginning of
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surveillance and preparedness planning using multiple modeling approaches. The successful candidate will develop and implement statistical and machine-learning models, integrate multi-source ecological datasets
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differential equation models of bacterial persistence. A particular challenge, both for simulation and for machine learning, lies in the high dimensionality of these equations, which causes grid-based numerical
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. The successful applicant will develop a predictive pipeline using atomistic modeling and machine learning to identify optimal "seeds" for directing crystal growth, followed by rigorous experimental testing
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, seeks to recruit a junior research scientist to develop AI-enabled healthcare applications. Key Responsibilities: Develop and fine-tune computer-vision models, instance segmentation, and retrieval-based
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issues. Proficiency in urban modeling tools such as MATLAB, Python (especially libraries like Pandas, NumPy, SciPy, GeoPandas, etc.), and R. Advanced skills in predictive modeling and machine learning