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/nguwxnmq601i9xtl3b Requirements Research FieldComputer science » Computer systemsEducation LevelPhD or equivalent Specific Requirements - Skills in machine learning and image analysis, with strong proficiency in
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following skills: Strong interest in the field of neuroimaging, psychiatry and genetics. Computer skills: Strong level in the main informatics software (FSL, Freesurfer, fMRIprep) and coding languages (R
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, preferably MRI. Experience with tumor segmentation, radiomics, or deep learning–based image processing is expected. Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow is required
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the ECHOES ERC project. The primary objective of this PhD is to develop and validate innovative post-processing techniques for the detection of exoplanets in coronagraphic images. Unlike traditional methods
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learning, deep learning, and LLM-based methods to multimodal clinical datasets e.g. EHR, imaging, omics, sensor data Designing and implementing NLP pipelines for clinical text processing, semantic annotation
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problems, statistical learning and machine learning (machine learning, deep learning) - Knowledge of associated software development tools and environments: Python, PyTorch, Scikit-learn, Jax, Julia
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on the development of advanced artificial intelligence and machine learning methods for genome interpretation, with a particular emphasis on modeling the relationship between genetic variation and phenotypic outcomes
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processing, neuromorphic engineering, or a closely related field. A solid background in machine learning is expected, with interest or experience in spiking neural networks, temporal modeling, or bio-inspired
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 27 days ago
. Picchini. Fast, accurate and lightweight sequential simulation-based inference using Gaussian locally linear mappings. Transactions on Machine Learning Research, 2024 Kugler, F. Forbes, and S. Douté. Fast
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anomaly detection using advanced and optimized methods. • Literature review (image processing, deep learning, vision-language models, diffusion models, etc.). • Generative AI for creating reliable models