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- Institut de Físiques d'Altes Energies (IFAE)
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assisting with in-situ TEM measurements, facilitating cutting-edge research in sustainability and energy fields. Part of the project will also include the development of deep learning frameworks for TEM image
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of inflation and phase transitions in the early universe. We are developing new data analysis methods like the use of deep learning and the use of robust statistics. This work is naturally extended to studying
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of inflation and phase transitions in the early universe. We are developing new data analysis methods like the use of deep learning and the use of robust statistics. This work is naturally extended to studying
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and paleosols 3) train and test deep learning algorithms. You will be required to take responsibility for all the steps involved in the “Phytolith analysis” work package of DEMODRIVERS. This will
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regulated training activities and contribute to continuous training activities. Conduct research that allows the development of new AI methodologies based on deep learning that allow for assisting musical
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to develop and implement machine learning/deep learning tools for personalized medicine in cancer by exploiting electronic medical records and medical images in relation to cancer diagnosis and the
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the LAMP group at the Computer Vision Center (CVC), in Barcelona, Spain. The position is for 2-3 years and linked to the project “Foundations for Adaptive and Generalizable Deep Learning” (EXPLORA
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. Familiarity with statistical modelling, machine learning and deep-learning Additional information: We offer: 🌐The opportunity to work with our state-of-the-art HPC infrastructure and to join a vibrant network
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. SILEX 2025) to calculate the Fire Radiative Power (FRP) and compare with satellite observations (VIIRS, SLSTR, FCI). Develop a fire front segmentation algorithm using machine learning techniques (deep