7 algorithms-"DIFFER"-"Foundation-for-Research-and-Technology-Hellas" Fellowship positions at INESC TEC
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benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: ● Research and develop novel reliable deep learning computer vision algorithms for the detection and quantification of GIM lesions
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to explore new optimizations, such as data deduplication, support for multi tenancy, and new scheduling algorithms. These optimizations should be implemented and integrated into the platform.; Implementation
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PRESENTATION OF THE WORK PROGRAMME AND TRAINING: 1. Literature review regarding inspection and quality control methods that are scalable over time and robust to different and new defects; 2. Identification and
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benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: Research and develop novel reliable deep learning computer vision algorithms for the detection and quantification of GIM lesions
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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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generation Energy Management Systems (EMS) to be integrated by different stakeholders, while demonstrating the value added of asset’s connection to common data space, reducing uncertainty and hence increasing
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waveguide setups and development of PCBs for reconfigurable intelligent surfaces (RIS).; 2. Implementation, testing, and optimization of RIS control algorithms on microcontroller-based platforms.; 3