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This project aims to advance representation learning in cybersecurity by developing deep learning architectures capable of extracting high-level, structured, and semantically meaningful representations from
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and able to manage your priorities. 🎓 We are looking for people with a PhD in machine learning, deep learning, data science, computer science, obtained less than 3 years before the date of hire, with a
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degree in computer science / mathematics /telecommunications / automatics, when starting the PhD. Programming: - Python language (required) - Deep Learning libraries (like TensorFlow, Keras, PyTorch
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project at the forefront of microscopy and bioimage analysis (https://www.msca-agile.eu/ ) and contribute to OMERO integration and optimization of Biom3d, a cutting-edge deep-learning framework for 3D image
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 18 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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effectiveness depending on image depth, and availability of multi-sectral information will be analysed. Related mathematical skills Basic knowledge of AI / deep learning methods is needed. Having some interest in
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related to staff position within a Research Infrastructure? No Offer Description You will join the GIN: https://neurosciences.univ-grenoble-alpes.fr You will be supervised by Julien BASTIN (Inserm Research
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atmospheric perturbations, and improving performance under realistic operational conditions. Main activities include: • Designing and developing deep learning models to correct wavefront sensor nonlinearities
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new insights into the phenomena observed and enrich the databases required for deep learning methods. The neural networks currently being developed at LISTIC to detect and segment areas of movement in