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Fundación para la Investigación Biomédica del Hospital Gregorio Marañón (FIBHGM) | Spain | 3 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
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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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of offers available1Company/InstituteFaculty of Computer ScienceCountrySpainGeofield Contact State/Province A Coruña City A Coruña Website https://www.udc.es/ Street A Maestranza 9 Postal Code 15071 E-Mail
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and modelling of omics, clinical and imaging data, development of reproducible pipelines, application of machine learning techniques, integration of multi-modal data, scientific publication and
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software. (0-35) Experience in the application of advanced machine learning techniques (e.g., graph neural networks, reinforcement learning, probabilistic models, or latent representations) to biomedical
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. 3 or more years of demonstrable experience in machine learning theory. Excellent teamwork and communication skills Fluent in English The candidate who has obtained the highest score in the selection
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the neurovascular space. Knowledge of neurovascular anatomy, acute stroke, endovascular treatments, neuroendovascular devices for the treatment of stroke. Ability to generate machine learning analysis of medical
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for enhanced durability, performing microstructural analysis and mechanical testing. Topology Optimization & AI Integration: Use AI and machine learning to guide structural and topology optimization, creating
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of the Alhambra and the Generalife. Project 2 — Machine learning for energetic-particle transport in thunderstorms This project explores machine-learning (ML) techniques to accelerate the numerical simula- tion
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. Recognised Researcher position has been opened. The ideal candidate holds a master's-level background in robotics, AI or related fields, with strong Python/C++ skills and experience in machine learning