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performance, yet their atomic-scale origin and role in reactivity remain poorly understood. The project addresses this open problem by integrating high-throughput Density Functional Theory, machine-learning
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of Barcelona; Particle Physics Phenomenology group. Main responsibilities / tasks: 1. Develop anomaly detection methods using Machine Learning and Simulation-Based Inference for high-dimensional parameter spaces
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, Telecommunications, Artificial Intelligence or Computer Engineering; Mathematics; or a related field. Training or experience in data science, deep learning, and artificial intelligence. Knowledge of Python, PyTorch
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The Center for Machine Learning Research (CMLR) is a newly founded interdisciplinary research center at Peking University. Its goal is to advance machine learning-related research across a wide
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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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-off companies. PROJECT SUPERVISOR & HOSTING GROUP Dr. Fernando Vilariño will be the supervisor of this position. He is the leader of the Quantum Machine Learning team (QML-CVC) at CVC. The Computer
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and Artificial Intelligence (CDAI) Support Unit. The successful candidate will be responsible for defining the institute's computational and data-driven strategy, integrating Machine Learning (ML
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, generalizable, and interpretable solutions using next-generation machine learning techniques. The applicant will work under the supervision of the principal investigator in the design, development, and evaluation
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/deploying deep learning models and machine learning applications. Computer skills: Python (PyTorch, TensorFlow), databases (MySQL), 3D Slicer, ITK-SNAP, OpenCarp. Previous experience in research activity in
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Fundación para la Investigación Biomédica del Hospital Gregorio Marañón (FIBHGM) | Spain | 6 days ago
, scikit-image, SimpleITK, etc.), will be given special consideration. Knowledge of machine learning and artificial intelligence techniques is a plus. Previous experience in code parallelization, the use