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through scholarship, professional practice, and leadership in professional and learned organizations. Applicants should submit a curriculum vitae and apply to requisition number 26001362 via: https
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neurological disorders, novel applications of deep brain stimulation technology to the treatment of neurological and psychiatric disease, the mechanisms of deep brain stimulation and finally motor and reward
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expertise, lived experience, and a deep understanding of carcerality and transformation. The ideal Deputy Director brings more than credentials—they bring lived insight, political clarity, and a global-local
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culture. This tenure-track position is dedicated to advancing cancer research through expertise in cancer data science, focusing on deep learning, artificial intelligence (AI), generative AI, large language
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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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to develop deep learning models for analyzing whole-slide histopathology images, as well as natural language processing (NLP) methods for clinical records such as pathology reports and electronic health data
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and memory, and with the design and implementation of cutting-edge data analysis pipelines that use deep learning to reconstruct perceived information from functional MRI in real time. For more
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development. You enjoy supervising and teaching and using your excellent communication skills to inspire the coming generation develop the same deep passion you have for quantum technology. You always have an
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 2 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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processing, quality control, integration, and analysis of single‑cell and multimodal omics datasets (e.g. scRNA‑seq, scATAC‑seq). Train, evaluate, and benchmark deep learning models operating on single‑cell