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Fundación para la Investigación Biomédica del Hospital Gregorio Marañón (FIBHGM) | Spain | 1 day ago
numerical models applied to patient-specific cardiac geometries. • Application of machine learning and artificial intelligence techniques to improve data processing and the integration of multimodal
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learning or multi-agent systems. Experience with cloud-native technologies (Docker, Kubernetes) or distributed computing. Experience with efficient neural architectures, scalable model design, or resource
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research, machine learning or artificial intelligence (e.g., large language models, EHR foundation models), causal inference (e.g., target trial emulation), and child health research. The research program
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demonstrated experience in computer vision or analysis of pathology images. The appointees will participate in a multidisciplinary collaborative research project related to development of deep learning model
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network structures. Methods from graph theory, machine learning, and artificial intelligence will be employed to model complex relational structures and identify patterns in high-dimensional data. The work
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of interest to BNL and the Department of Energy (DOE). Topics of particular interest include: (i) development of novel machine learning models and adaptation of existing approaches for scientific applications
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: Applied mathematics; Machine Learning; Mathematical Modelling Appl Deadline: 2026/03/24 10:59 PM UnitedKingdomTime (posted 2026/03/18 04:00 AM UnitedKingdomTime, listed until 2026/04/01 04:59 AM
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Computational Mechanics. Solid background in continuum mechanics and numerical modeling Strong interest in machine learning and scientific computing Experience with numerical methods for PDEs and data-driven
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to reduce the cost of clean hydrogen to $1/kg by 2031. The project proposes to address key scientific challenges by using molecular simulations (reactive force fields like ReaxFF and machine learning
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based on machine learning tools for energy problems related to prediction. The application domains include both industry and climate changes. The first two months will be devoted to the study of