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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | 6 days ago
to motion and respiration. Over the past years, we led several works in this area. Particularly, we developed several deep learning models for the segmentation of SC lesions either from T2 sagittal MRI
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Université Grenoble Alpes, laboratoire TIMC, équipe GMCAO | Grenoble, Rhone Alpes | France | 2 months ago
with expertise in medical image processing—particularly registration and segmentation—and proven experience in deep learning, with a focus on ultrasound imaging. Prostate cancer diagnosis relies
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(including computer science, machine learning or deep learning). Activities Description of the research activities : The post-doctoral researcher will develop the research actions defined in his/her research
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) About the Project Deep learning models, and in particular large language models (LLMs), have demonstrated remarkable capabilities but remain limited by their heavy computational requirements, lack
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), whose objective is to extend the HLA-Epicheck model, originally developed within the framework of a PhD thesis, and to implement new deep learning approaches to assess donor–recipient compatibility in
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Processing Skills required: - Medical computer programming: python, 3D slicer, LCmodel (optional), FSL, spm, ants) - Artificial Intelligence skills and deep learning experience - Proficiency in Tensorflow
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, statistics, machine learning and deep learning. The project Motivation: Interpreting the genome means modeling the relationship between genotype and phenotype, which is the fundamental goal of biology
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in the Earth's outer core, with implications for deep Earth processes [1]. A variety of inverse methods (data assimilation, machine learning, etc.) has been employed to recover the fluid motions in
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Machine/Deep learning and classification Knowledge of the Linux operating system for using a computing cluster Interest in transdisciplinarity and teamwork Autonomy and scientific rigor Website
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, robustness under varying turbulence, and autonomy for distributed systems. To address this, the group integrates Artificial Intelligence into AO control loops, using deep learning to handle sensor