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Field
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will be part of a research environment focusing on integrating multi-source satellite remote sensing data and developing novel algorithms to quantify agroecosystem variables for environmental
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between various imaging modalities and multi-omics during aging and development. • Implementing computationally intensive algorithms on high-performance computational clusters
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industrial imaging data. You will directly contribute to developing and deploying algorithms for multi-modal tomography (X-ray, neutron, and electron), advancing methods for non-destructive evaluation (NDE
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, physics-informed control, and digital twin technologies. Project description The project focuses on the development of robotic methods for plant health monitoring that combine robot–plant interaction with
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these interactions and their evolution are studied, with a few privileged fields that are particularly sensitive to these interactions, whether local or global. Each of these socio-ecosystems is used as a laboratory
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comparative embedded ethics approach, examining neuroAI development in both clinical neuroscience and neurorobotics settings. Your tasks: The postdoctoral researcher will play a central role in the project and
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, containerization (Docker), Kubernetes API development and web-based analytics tools Systems, Optimization, and AI ML/AI for mobility prediction and optimization Graph algorithms, network science Spatiotemporal
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will
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(IoT) devices, for producing information on the status of natural resources. Our research and development activities focus on the synergistic use, processing, and interpretation of data from multiple
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research knowledge by participating in educational opportunities; reading professional publications; maintaining personal networks; participating in professional organizations. · Use and continually develop