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knowledge in building ventilation systems, heat transfer, fluid dynamics, machine learning, data analysis, and coding e.g., Python. Understand sensors, actuators, data acquisition, and control systems
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Department of Computer Science and Computational Engineering, and the Department of Geosciences. Research infrastructure is provided via existing data, sensor networks, and established field sites along
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instrumentation, physical modelling, sensor technology, or experimental validation is advantageous. Experience with three-dimensional modelling, computer-aided design (CAD), or additive manufacturing (3D printing
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validation of the solutions being created. Activities will include the selection and integration of sensors and data acquisition systems, the implementation of algorithms for data compression and analysis, and
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). 5. Develop sensor fusion and navigation (e.g., IMU, vision, GNSS/DVL/encoders), with fault robustness 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: 1. Multi-platform reference architecture
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;Knowledge in the collection, processing, and analysis of data obtained from physical activity and exercise monitoring technologies (e.g., wearables, sensors, or equivalent systems);Knowledge of exercise
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prioritization of maintenance. The project aims to develop an integrated decision-support framework that combines inspection images, sensor data, and engineering interpretation to enable more transparent, evidence
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inspection images, sensor data, and engineering interpretation to enable more transparent, evidence-based maintenance decisions. Your main duties and areas of responsibility will be to A large portion of
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of the sensor infrastructure itself using reverse estimation techniques.; The fellow will collaborate with the Robotics and Autonomous Systems Center team on the development, integration, and validation