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Field
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of deep learning in many disciplines, particularly computer vision and image processing. Consequently, coding architectures based on deep learning and end-to-end optimization have been proposed [Ding 2021
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Scheduling, Real-Time Systems, Network Calculus, Robustness, Machine Learning, Industrial Networking Note: This thesis topic may not be appropriate for candidates seeking a career in the data and AI domain
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the "Machine Learning and Gene Regulation" team led by William Ritchie, specializing in bioinformatics and post-transcriptional regulation. The scientific environment at the IGH — international seminars, journal
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support machine learning applications for analyzing electron microscopy images of nanoalloys. Model interactions between nanoalloys and carbon substrates to reflect experimental conditions, incorporating
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 2 months ago
skills Specific Requirements The candidate must hold a PhD in machine learning and have strong mathematical skills. Knowledge of bandit models is a plus. LanguagesFRENCHLevelBasic LanguagesENGLISHLevelGood
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Essential skills, knowledge and experience: Experience with machine/deep learning development Data-Centric AI Knowledge Notions of cybersecurity and networks are optional Spoken and written English Desirable
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biology skills Experience with single-cell RNA-seq analysis Experience with machine learning based methods Have evidence of scientific accomplishment via peer-reviewed publications Understanding of cancer
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). - Familiarity with machine learning principles and generative/classification models (PyTorch Lightning, torch, scikit-learn, etc.), as well as data/model analysis methods (PCA, t-SNE, etc.). - Proficiency in
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preparatory cycle), the engineering cycle as a student and/or apprentice, and the Master’s degree programme (M1 and M2). He/she will primarily contribute to teaching computer architecture and microprocessors
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; _Foundations in artificial intelligence (symbolic AI, machine learning, multi‑agent systems, or data analysis); _Interest in governance, safety, trust, and validation of AI‑based systems; _Programming skills and