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of 3D crystalline structures; – depending on the candidate's profile, implementing machine learning methods (AI & machine learning) for the analysis of physicochemical data from the hpmat.org database
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. In particular, he/she will be expected to :• Select and evaluate the most suitable approaches from the wide range of machine learning and computer vision methods available in the literature, with
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responsibility of developing predictive tools based on machine learning for the analysis and interpretation of Raman vibrational spectra applied to battery materials. The successful candidate will design and
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 13 days 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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automated configuration mechanisms based on fingerprinting and machine learning to ensure traffic analysis remains faithful to the behavior of the monitored machines. Finally, you will validate your solutions
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at the crossroads of AI, machine learning, bioinformatics and genomics, and in developing new methods rather than just applying existing ones, we'd like to hear from you. Website for additional job details https
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, France [map ] Subject Area: Machine Learning / Machine Learning Appl Deadline: 2025/12/13 04:59 AM UnitedKingdomTime** (posted 2025/10/21 05:00 AM UnitedKingdomTime, listed until 2026/04/22 04:59 AM
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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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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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. In this project, we aim to develop digital tools combining density functional theory (DFT) and machine learning (ML) to accelerate the in-silico design of solid catalysts for the DA process. - Perform