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Field
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Mission: Support research to improve the management of renewable energies. Functions to be developed: Develop machine learning algorithms. Implement and validate computational models. Plan networks with
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established lasting ties with industrial partners and created several spin-off companies. CONTEXT AND MISSION We are seeking a postdoc to join the Quantum Machine Learning team (QML-CVC) in beautiful Barcelona
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methods for uncertain data, including variational autoencoders for the generation of coherent surrogate datasets with incomplete or imprecise information. Implementation of similarity-based learning and one
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Research Infrastructure? No Offer Description Este contrato es parte del proyecto Machine learning optimization of heat pump architectures based on wireless power transfer sensors with high gain antennas
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Technologies, Computer Engineering, Artificial Intelligence or a related field. Training or experience in data science, deep learning, and artificial intelligence. Knowledge of Python, PyTorch, Numpy, HugginFace
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and/or experience in machine learning, deep learning and data science. Training and/or experience in signal processing, specially audio, images and biomedical. Knowledge of Python, PyTorch, TensorFlow
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, implementation, and testing of deep learning algorithms for speech and audio processing. Implementation of systems for participation in competitive technology evaluations. Where to apply Website https://www.uam.es
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or experience in Deep Learning and Artificial Intelligence. Proficiency in programming languages: Python, Numpy, Pytorch, Tensorflow. Training or experience in speech and audio processing. Specific Requirements
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/Qualifications Graduate in Telecommunications or a related field. Training and/or experience in machine learning, deep learning and data science. Training and/or experience in data and signal processing, specially
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The Center for Machine Learning Research (CMLR) is a newly founded interdisciplinary research center at Peking University. Its goal is to advance machine learning-related research across a wide