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Fundación para la Investigación Biomédica del Hospital Gregorio Marañón (FIBHGM) | Spain | 7 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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fellows will receive joint mentorship from leading experts in metabolic biology, AI and machine learning, drug delivery, and translational medicine, while maintaining full academic independence in research
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include an FC150 bump-bonding machine, a Pac Tech SB2 solder deposition machine, an F&K Delvotec automatic wire bonding machine, and a dedicated lead-shielded room for sensor characterization with radiation
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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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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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. 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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. 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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, etc.) o Energetic frustration or protein energy landscape analysis o Machine learning in protein science o +2 years of experience after PhD Knowledge of evolutionary biology concepts (phylogenetics
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performance with classical methods. Qualifications PhD in Physics, Computer Science, Applied Mathematics, or related fields. Strong background in at least one of the following: machine learning, quantum