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Field
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-depth expertise in Computer Vision and Photogrammetry. - Mastery of state-of-the-art Neural Rendering (NeRF, NeuS, SDF). - Knowledge of Photometric Stereo methods. Operational Skills: - Advanced
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Materialist theories Developing appropriate (design) research methods Project management About the project:Thinking with Things is funded by the Austrian Science Fund (FWF) and will start on January 1, 2026. It
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | about 19 hours ago
the data payload size and lead to inefficient resource use. Consequently, grant-free methods [1] that eliminate or reduce control traffic are well suited for these scenarios. Removing coordination
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Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig | Leipzig, Sachsen | Germany | about 4 hours ago
institute of the Max Planck Society and is dedicated to the study of human cognitive abilities and brain processes as well as the development of neuroimaging methods. The Brain Networks Group, led by
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analytical methods and digital capability for data consumption, organization, validation, storage, and classification of electronic health data. Job Duties Develops analytical methods and digital capability
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and contribute to a team environment. Technical Proficiency: Skilled in using office software, technology, and relevant computer applications. Communication: Strong and clear written and verbal
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18 Nov 2025 Job Information Organisation/Company UNIVERSITE DE TECHNOLOGIE DE COMPIEGNE Department Department of Computer Engineering Research Field Engineering » Control engineering Researcher
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of computer codes. Specific Requirements Educational Requirements: Knowledge of mathematical and computational modeling with partial differential equations and the finite element method. Scientific programming
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Two-year postdoc position (M/F) in signal processing and Monte Carlo methods applied to epidemiology
and data-driven procedures for pointwise and/or credibility interval estimation of epidemiological indicators, e.g., for the reproduction number R(t) of Covid19. Elaborating on a recent epidemiological
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to be addressed. Matrix completion methods have proved to be efficient when reconstructing a non fully observed data. These methods can be applied to complete or predict links in a network. However