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machine learning models that predict soil health and crop performance. The position will exploit datasets integrating biochemical and molecular soil parameters (with a focus on microbiome features from
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. The successful candidate will be joining the Quantum Optics Theory group led by Prof. Dr. Maciej Lewenstein. The successful candidate will work on Machine Learning research. Share this opening! Use the following
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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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“Heterogeneous Advances in Machine Imitation Learning for Training Orchestrated Navigation (Hamilton)” The CVC offers one pre-doctoral fellowship linked to the project “Heterogeneous Advances in Machine Imitation
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, computer science, computer engineering or related subject. We will positively consider previous background in computer vision, deep learning and/or color image processing, as well as previous experience in research
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incorporates probabilistic prediction models and hybrid optimization and machine learning techniques. This approach will enable the efficient assessment, planning, and offering of flexibility in scenarios
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Description Develop the doctoral thesis focused on Quantum Computing and Machine Learning for Power Systems Where to apply E-mail monica.aragues@upc.edu Requirements Research FieldEngineering » Industrial
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apply statistical and machine learning models to identify predictive markers of depression. Design and execute experimental protocols related to self- representation and chronic pain. Prepare manuscripts
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research 0 A5 Experience and training in managing techniques and methods necessary for the execution of the project: - Computational neuroscience and machine learning 20 A6 Stays at universities and/or other
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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