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deep learning, on the topic “Analysis and Reconstruction of Digital Data Fragments”. This internship is intended for students at M2 level, or in the final year of an engineering school, interested in a
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FieldMathematicsYears of Research ExperienceNone Additional Information Eligibility criteria PhD in computer science, deep learning, or data science. Experience with multimodal models for biological data. Website
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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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York University Overview The NYU Entrepreneurial Institute's Assistant Director of Research Commercialization leads programs and initiatives designed to accelerate the commercialization of deep
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, as well as from industry. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/294560/phd-research-fellow-in-deep-learning-for-medical-imaging-and-multi-modal-data-in
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Engineering, Mechatronics, Computer Science, etc. Strong background in AI, Vision Language Model, end-to-end autonomous driving, deep learning, computer vision, robotics and automation. Candidates having
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to biological data. PREFERRED QUALIFICATIONS: PhD in Bioinformatics, Computational Biology, Computer Science, or a related field Experience applying deep learning or foundation-model approaches to sequence-based
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applications for a fully funded postdoctoral associate position. This position, available immediately, focuses on developing machine learning and deep learning methods for analyzing large-scale single-cell DNA
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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
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modeling with deep learning for the analysis of hyperspectral imaging data. The researcher will be responsible for the design and development of numerical models, including neural network architectures