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Field
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creation of a database for the various pollution sensors with a view to training online (non-embedded) models in the first instance. - Development of a machine learning algorithm based on the study database
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. The postdoc will develop machine learning algorithms to analyze phenotype and sequence data, as well as active learning algorithms to optimize and control experiments in directed evolution. This position
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We are looking for a Research Fellow to conduct the research for the project entitled “Manual Assembly Job Quality Inspection”. The role will focus on research and development of AI algorithms
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- Simulación en entornos virtuales para el estudio de algoritmos de clasificación de objetos y generación de datasets ------------------ - Implementation of algorithms in embedded processing systems for train
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LEO, MEO, and GEO constellations), and complementary on-board sensors. Research will investigate algorithms for robust multi-sensor fusion and positioning assurance. A strong emphasis will be placed
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and algorithms for event-based fusion of two physically-colocalized event-based and depth vision sensors, simulate and analyse these models, and explore possibilities to realize them in CMOS ASICs
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Toolkit customization, and performance tuning under hardware constraints; collaborating on robot motion planning, path optimization, and sensor data processing algorithms; implementing and testing ROS nodes
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influenced corrosion (MIC) in marine environments. It uses AI-supported models, Bayesian data fusion, and real-time sensor data integration. Your responsibilities include: Development of a digital twin (DT
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algorithm-driven sensing systems, remote sensing and multi-modal sensor integration Applicants do not need to cover all areas listed above but should bring strong expertise in at least one and a broad
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evaluation of algorithms for: perception in robotics; sensor based control and navigation ; interactive mobile manipulation; multi-sensor data modelling and fusion. This job offer takes place within