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Field
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 5 hours ago
. Recent updates to QFED include integration of fire products from new sensors (VIIRS), and a new multispectral approach for retrieving fire radiative power (FRP) for two phases of burning: flaming and
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sensing; support in choosing tip geometry, stud magazine, and interfaces to the vacuum chamber). • Co-development of algorithms for optimal welding (trajectory and force planning, adaptive parameters
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of integrated and inertial navigation. The working group deals with multisensor systems, i.e. the sensor fusion of GNSS (GPS, Galileo, GLONASS, Beidou), INS (inertial navigation system), cameras, LiDAR (light
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intelligence (AI) and machine learning(ML). Duties This position combines knowledge of the Earth observation (EO) domain (EO instruments, EO data, EO algorithms, modelling, etc.) and AI/ML, as well as data
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. Local slopes of a perturbed wavefront (for example, after propagation through turbulence) can be sensed using such a filter and a camera. From the measured slopes, the well-established algorithms used in
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-resolution wearable sensor streams, and endocrine test outcomes. Intelligent Artifact Detection: Develop cutting-edge Machine Learning algorithms to automatically identify, flag, and mitigate data artifacts
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) sensor data. This will be a small system-on-chip designed to operate on the edge (i.e. close to the sensor). The project will explore whether emerging logic-based ML algorithms can be translated
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to operate on the edge (i.e. close to the sensor). The project will explore whether emerging logic-based ML algorithms can be translated into smaller, faster, more energy efficient and cost-effective hardware
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decision-making. Examples include crowd management and large-scale communication networks based on cellular or wireless sensors. For instance, during mass gatherings such as the sport matches (e.g
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to optimise built-environment thermodynamics and occupant comfort by creating predictive AI tools for spatiotemporal heat transfer. Machine learning algorithms will identify energy inefficiencies and propose