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INESC TEC is accepting applications to award 4 Scientific Research Grant - NEXUS - CTM (AE2025-0564)
; - survey and analyze the state of the art in emerging wireless networks, including simulation aspects; - collaborate in the preparation of technical reports on the algorithms, mechanisms, models
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the preparation of technical reports on the algorithms, mechanisms, models, or protocols developed; - collaborate in the development of new communications solutions for extreme environments; - contribute to co
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simulation of algorithms for detecting intermittent faults in compensated networks. Identification and testing of conditions for selective protection of intermittent faults in meshed and radial networks
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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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clothoid-specific algorithms that generate a speed profile that takes into account the characteristics and properties of the applications, applied to the movement of human arms/hands, human locomotion, and
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process and the results obtained. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: - To contribute to the specification and development of algorithms for optimizing energy systems with
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satellite data analysis algorithms and solutions that will form the technology foundation for new products. The position is for a period of three years. Admission to the PhD programme is a prerequisite for
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visualisation (libraries such as Three.js, OpenGL, VTK, or similar); - Advanced knowledge of optimisation algorithms; - Previous experience with software development for logistics problems; - In-depth experience
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algorithms to combine information on cardiovascular activity obtained from heart sound signals, electrocardiogram, and photoplethysmography. Investigate the inclusion of prior knowledge about the application
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distributed systems. Minimum requirements: - Solid knowledge of database engine implementation; - Solid knowledge of optimization algorithms (Volcano/Cascades); - Practical development experience with