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analysis, and data visualization. Apply advanced statistical, machine learning and AI methods when appropriate. Review analysis outputs and ensure methodological consistency and quality. Collaborate with
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técnicas de machine learning e IA. Sólidos conocimientos en análisis y tratamiento de datos, programación y desarrollo de modelos analíticos. Experiencia con bases de datos y herramientas de análisis
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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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intelligence, data science, medical physics, neuroimaging, bioengineering, or related disciplines, accompanied by accredited training in machine learning, deep learning, or medical image analysis. Experience: A
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analysis, computer vision, or machine learning, with a clear interest in developing image analysis algorithms and an affinity with medical topics. Good communication and organizational skills are essential
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learning and deep learning. Specific Requirements PhD in acoustics. Knowledge of acoustical measurement techniques, as well as physical acoustics. Some experience in acoustic signal processing and machine
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. The successful candidate will be involved in the gravitational wave astronomy research area as part of the GRAVITY research group, within the framework of the project "Ground-based Discovery Machines
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practical knowledge of statistical and programming packages is mandatory, including R, Python, and/or SQL. Extensive experience with advanced statistical techniques and algorithms, such as Machine Learning
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for a short-term 2.5-month postdoctoral position (full-time) focused on developing and validating machine learning models that predict soil health and crop performance. The position will exploit datasets
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, engineering or physics. Knowledge: Computational programming, machine learning, quantum transprot, device simulation. Professional Experience: use of device simulation codes applied to 2D materials. Personal