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on two core but complementary areas: Computer vision and sensor data analysis, applied to tasks such as object detection in drone images (e.g., pest or disease detection), object tracking (e.g. leaves
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doctoral degree (or expected completion within a few months), for example in economics, regional science, economic/quantitative geography, mathematics or related field demonstrated knowledge and experience
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properties (IOPs/AOPs) for the German Baltic Sea coastal region. This will serve as a training data set for AI-driven simulations in the SEAGUARD project and contribute to the analysis of drivers of change in
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control and optimization of electrolysis from the cell to the stack requires automated monitoring, analysis, and control of the operating parameters and processes. As part of this project, the potential
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) at the Technical University of Munich (TUM) is looking for a talented postdoctoral researcher (f/m/d) to deepen their expertise and interest in machine learning for medical image analysis and built their early
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(MUCCnet: atmosphere.ei.tum.de ) Optimization of an urban sensor network configuration for greenhouse gas and air pollutant measurements using mathematical and physical assessments Analysis of ground-based
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14.12.2022, Wissenschaftliches Personal The BMBF-funded position is part of the CoMPS project, which is a multidisciplinary project combining the fields of mathematics, computer science, geophysics
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• Information-theoretical analysis of entanglement-supported classical communication, • Encoding protocols for entanglement-assisted classical communication, • Protocols for interleaving transmission in networks
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(ML4Earth). AI methods, and especially machine learning (ML) with deep neural networks have replaced traditional data analysis methods in recent years. The Technical University of Munich (TUM), together