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Autónoma de Madrid, and funded by the Community of Madrid. Among the tasks to perform are: Management and preprocessing of audio databases. Design, implementation, and testing of deep learning algorithms
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innovative research in three major categories: AI Fundamentals: machine learning, deep learning, data science; AI Core Applications: computer vision, natural language processing, speech processing, robot
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specialised libraries (TensorFlow, PyTorch, scikit-learn, Pandas). Knowledge of machine and deep learning methods and techniques, including training, adjustment and development of language models and LLMs
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, spectropolarimetric inversion techniques, and machine-learning–based approaches, for the physical interpretation of solar images and spectral profiles. Special consideration will be given to applicants with experience
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to the topic, including food safety, microbiology, computational biology, machine learning, artificial intelligence, data science, or other related scientific fields. Familiarity with data-driven
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, multilevel analysis). Knowledge in developing predictive and forecasting models in health or environmental research. Skills in machine learning or AI techniques for prediction of complex outcomes. Experience
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=50415 Requirements Research FieldPhysicsEducation LevelPhD or equivalent Skills/Qualifications Advanced skills in Machine Learning and Artificial Intelligence Proficiency in spoken and written English
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: Education: Bachelor in Biosciences, or Engineering degree in Computer or Data Sciences. PhD in bioinformatics, data sciences, machine learning or related areas. Experience: previous experience working with
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characterized as an inability to emulate basic human vision skills. Despite significant advances in deep learning-based computer vision systems, many limitations still exist. The main objective of this project is
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platforms. Experience in development of digital twins or physics-informed machine learning models. Experience in programming (e.g., Python or equivalent) and development of control or data acquisition