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for this research work is divided into the following phases: 1) Collaboration in annotating a set of data, with a view to creating learning sets for Machine Learning models. 2) Evaluation of performance with respect
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networks, retrieval-augmented generation (RAG), and model fine-tuning. The candidate should have the ability to instruct and mentor master’s students in data science and engineering on effective problem
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contribute to developing this theoretical framework, with a strong focus on analytical modeling, computational methods, and the interpretation of learning signals embedded in physical structures. Recent
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*• Experience in Python or another programming language (projects, GitHub repositories, courses, scientific use).• Training or experience in machine learning and data science applied to environmental or energy
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computational models, applying statistical and machine learning methods, and integrating data across modalities to generate novel scientific insights. The Postdoctoral Fellow will lead manuscript preparation
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innovative machine learning architectures for the mining, prediction, and design of enzymes. Combine state-of-the-art ML (e.g., deep learning, generative models) with computational biochemistry tools
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-France 75 005, France [map ] Subject Areas: Machine Learning Statistical Physics Appl Deadline: 2026/01/16 04:59 AM UnitedKingdomTime (posted 2025/11/04 05:00 AM UnitedKingdomTime, listed until 2026/05/05
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diffraction data where the information extends towards 3-d space. Machine learning offers promising approaches for the solution of complex problems of disorder, ultimately aiming at general and automated
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Assistant Professor - Information Systems, Operations Management, Supply Chain Management, and Busin
AI/ML methodologies , advanced analytics , and data-driven decision making to solve contemporary business challenges. Research methods of particular interest include machine learning , deep learning
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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