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The successful candidate will contribute to the development of a new generation of 3D-printed biomimetic materials designed to model the human intestine in vitro, as part of the BAM-INT project. The project aims
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Bio Process Development Unit (ABPDU ). In this exciting role, you will develop AI-driven predictive metabolic models of cell physiology, metabolism, and functional behavior. You will have the
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Apply and further develop a novel coupled model for hydrothermal multi-phase fluid flow, magma evolution, dynamic permeability and well configurations Actively collaborate with project partners in mutual
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Join TUNED and develop the models that will enable engineers to design tunnels in deep clay formations - an essential step in the Netherlands' journey towards safe, long-term disposal of nuclear
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deep learning has led to the emergence of Transformers-type networks whose performance has revolutionized the field. These networks are the basis of next-generation image processing models (such as
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Computing and Mathematical Sciences Division - Postdoctoral Researcher: CryoSTEM Foundation Models Mohamed bin Zayed University of Artificial Intelligence Location Abu Dhabi, UAE Open Date Jul 14
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architecture of entirely new foundation models, directly advancing the frontier of computational biology and machine learning. You will also implement parallel systems capable of training such models across
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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Infrastructure? No Offer Description → Apply until 01/09/2026 (DD/MM/YYYY) 23:59 (Brussels time) → Faculty of Bioscience Engineering → Department BW26 - Data analysis and mathematical modelling → AAP
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 13 days ago
inform representations and encoder adaptations. This activity will provide hands-on experience in making three-dimensional vegetation structure accessible within data-driven geospatial modeling processes