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decision-making across diverse applications in computer vision and data analysis. Where to apply Website https://aunicalogin.polimi.it/aunicalogin/getservizio.xml?id_servizio=1079 Requirements Additional
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from Hi-C and Capture Hi-C experiments. Have experience developing graphical user interfaces (GUIs). Candidates with knowledge or experience in machine learning methods will be prioritized. Successful
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competency models in collaboration with content experts. Develops and analyzes the Learning Needs Assessment for the department and clinical areas. Monitors compliance related to mandatory staff education
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competency models in collaboration with content experts. Develops and analyzes the Learning Needs Assessment for the department and clinical areas. Monitors compliance related to mandatory staff education
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simulations with machine learning models derived from experimental data. 1) Functional Knowledge and Technical Expertise (50%) a. COMSOL Modeling: Design, build, and run COMSOL Multiphysics simulations to model
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development in topics such as computer vision, audio signal processing, machine learning, deep learning, and/or sensor systems. Experience in collaboration and technology transfer to partners outside
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School graduates over a thousand students who are ready to take on great ambitions and challenges. For more details, please view: https://www.ntu.edu.sg/eee We are looking for a Research Assistant to carry
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between Numerical Analysis and Machine Learning, with a focus on physics-informed machine learning. The goal is to design learning strategies that embed the structure of governing physical laws, enabling
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Institut Pierre Louis d'Epidémiologie et de Santé Publique (IPLESP) | Paris La Defense, le de France | France | about 2 months ago
a postdoctoral researcher to work full-time on the DiscoReel project. The postdoc will work on developing machine and deep learning methods for epidemic modeling, integrating them with mechanistic
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competitive ERC. The project focuses on the development of a first-principles, machine-learning-accelerated computational framework for modelling polymorphism, anharmonicity, and electron–phonon interactions in