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with heat pumps/HVAC and EMS/BMS/SCADA, specifying data exchange and developing APIs; • support prototype tests, calibration and KPI definition (efficiency, cost, CO₂); • attend a transversal competences
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algorithms; - Automation of the model customization process by conducting laboratory tests.; - Improvement of the data workflow for real-time processing and sharing.; - Data collection in experimental and real
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of functional tests to validate the system’s performance and compliance.; • Preparation of the technical activity report within the scope of the research grant.; 4. REQUIRED PROFILE: Admission requirements
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of a multi-modal dataset.; - Implementation of a software module for storing datasets according to a pre-defined standard.; - Development of routines for testing existing ML algorithms on a multimodal
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and testing solutions in a simulated clinical environment, ensuring the applicability of the developed models in clinical practice.; 4) Participate in the analysis of results and benchmark the system
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algorithms for analyzing electrocardiography, electromyography and movement signals, identifying characteristics and recognizing patterns in everyday activities. Testing and validation of methods developed in
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under realistic conditions.; • Implement and experimentally test the system in a real environment, with hardware integration and validation campaigns in parabolic flights.; • Evaluate system performance
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pattern recognition Integration into a mobile application for the user Testing and validation of the developed software in a controlled laboratory environment Scientific article for publication in a journal