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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 4 days ago
dynamics data and advanced graph-based deep learning models to decode long-range communication pathways within macromolecular complexes. The PhD candidate will play a central role in this effort by
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Experience with MATLAB/Simulink, including Control System Toolbox, System Identification Toolbox, or Deep Learning Toolbox. Understanding of battery systems, electrochemical energy storage, or battery
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expertise. 2. Curriculum Vitae including a list of publications (maximum 3 pages). Where to apply Website https://jobrxiv.org/job/phd-position-in-machine-learning-and-ecology/?utm_sourc… Requirements
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E-mail jakub.ceranka@vub.be Website https://jobs.vub.be/job/Elsene-PhD-in-'medical-image-analysis-and-artificial-in… Requirements Research FieldEngineering » Biomedical engineeringEducation
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) and define the problem mathematically. Secondly, a central component of the PhD will be to learn mappings between heterogeneous spaces through latent-variable models and representation learning. Some
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Doctoral Researchers (PhD students) to work on deep learning methodologies for machine and robot perception. These positions are funded by the Horizon Europe project OPERA (Open Perception, Learning, and
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investigate deep learning architectures capable of learning microstructure-property mappings, including convolutional neural networks for microstructure image analysis, graph-based representations
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 4 days ago
mathematical background. - Familiarity with deep learning frameworks such as PyTorch. - Commitment, team working and a critical mind. - Fluent verbal and written communication skills in English
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applied methodologies in Data and Image Analysis, Computational Imaging, Statistical Learning, Uncertainty Quantification, Robust Estimation, and Deep Neural Networks. The group combines expertise in
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, IEEE INFOCOM 2020 [12] D. Bega, M. Gramaglia, M. Fiore, A. Banchs, X. Costa-Perez, DeepCog: Cognitive Network Management in Sliced 5G Networks with Deep Learning, IEEE INFOCOM 2019 [13]https