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- Computer Vision Center
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resonance imaging) Fluency in English Experience and knowledge: Required: Experience in computer programming Expertise in Python programming for Machine and Deep Learning, e.g., sklearn, pytorch, tensorflow
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implementation of artificial intelligence models (machine learning, deep learning, and adaptive learning) applied to the sensorimotor control of a bionic arm prosthesis. • Advanced processing of neural (EEG) and
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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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analysis will not be considered. Programming Skills in Python, R, MATLAB Prior knowledge of Statistics and Machine Learning Competencies and skills: Communication, Teamwork and collaboration, Commitment
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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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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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Skills/Qualifications Technical Competences: Programming: Python, Java, JavaEE, JavaScript, R, Android. Machine learning/AI frameworks: PyTorch, TensorFlow. LLMs (Large Language Models): Prompt Engineering
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sustainability of biomaterial manufacturing through safe design methods, machine learning, and predictive life cycle assessment as well as developing machine learning and hybrid digital modeling methods, combining
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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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, members of the Vision, Language and Reading research group at the CVC. For more information visit: http://vlr.cvc.uab.es/ THE COMPUTER VISION CENTER The selected candidate will work in the Computer Vision