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Field
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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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. 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
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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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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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and R&D into both computer and computational science (life, earth and engineering sciences) under one roof, and currently has over 1000 staff from 60 countries. Look at the BSC experience: BSC-CNS
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based on neutral atom platforms, exploring both theoretical and experimental domains. Research will span quantum control, quantum-enhanced machine learning, and hybrid quantum-classical computation
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development of analytical solutions, data analysis and machine learning. Candidates should have a demonstrated record of scientific publications in international journals and participation in conferences
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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
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infrastructure (e.g. Observatorio del Roque de los Muchachos) Hands-on training in cutting-edge techniques, from detector R&D to advanced data analysis and machine learning. Attendance to international