237 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "Ulster University" Postgraduate scholarships
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Your Job: We are looking for a PhD student to contribute to the development of fast, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular
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Infrastructure? No Offer Description Work group: IAS-8 - Datenanalyik und Maschinenlernen Area of research: PHD Thesis Job description: Your Job: We are looking for a PhD student in machine learning to work within
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modeling and model–data fusion techniques, and developing faster, machine-learning–based tools that can stand in for slow model simulations. These tools will be used to test how model parameters influence
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, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular geometries. Current simulation-based approaches require complex 3D meshes and are often too slow
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Your Job: We are looking for a PhD student in machine learning to work within a project linked to the “Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE)”. Your Job: Develop 3D+t
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models, which are essential for understanding climate change impacts. The work involves reviewing existing modeling and model–data fusion techniques, and developing faster, machine-learning–based tools
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, if applicable. It is expressly mandatory to use the FCT logo available at http://www.fct.pt/logotipos/ and, when applicable, the logos of the European Union and the Operational Programme, following the graphic
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sound understanding of data evaluation Prior experience with single-cell data analysis, network analysis, or machine learning are a plus Good organisational skills and ability to work both independently
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justified, recorded in minutes, and published on https://apply.uc.pt/ . VII.IX - Jury Composition: President: Luís Alberto Proença Simões da Silva Effective Members: Aldina Maria da Cruz Santiago, Carlos
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. The successful development of a Digital Twin-enabled IDS will not only improve the cybersecurity of industrial networks but also establish a foundation for further advancements in intelligent, self-learning