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these. We conduct research within nanophotonics, lasers, quantum photonics, optical sensors, LEDs, photovoltaics, ultra-high speed optical transmission systems, bio-photonics, acoustics, power electronics
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. Design, test, and document computational frameworks that combine 4D point cloud data, geospatial analysis, and advanced ML/DL algorithms. Integrate dynamic environmental datasets into immersive and
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, integration, and analysis of large, diverse datasets obtained from Unmanned Aerial System (UAS), Satellite imagery, ground sensors, and field measurements. -The candidate will work on Texas Climate Smart
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the budget of the project Development of AI-sensorized bionic prostheses, operation no. 17309, with project code 11.12 of the Physics Department/i3N at the University of Aveiro, funded by ANI through the P2030
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methods for multimodal imaging and real-time analysis in colorectal cancer screening and treatment. They will contribute to the design of AI algorithms for polyp detection, tissue characterization, and
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sensing, IoT sensors, and climate models. Design and implement deep learning models for forecasting extreme weather events such as floods, droughts, and heatwaves, integrating probabilistic approaches
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of the AI algorithms. Key duties Develop a robust framework to simulate streamflow decomposed into fast-flow and baseflow at multiple Moroccan watersheds. The candidate would have to test various fast-flow
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, telecommunications or related field. Other requirements include Strong background in communication theory, signal processing, and wireless communications, Extensive experience in physical (PHY) layer algorithm design
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, complex systems. Strong communication and writing skills; ability to work both independently and as part of a team. About the team The DATA team develops foundational mathematical and algorithmic approaches
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/S0022112006003429 [2] A. Cahuzac, et al. “Smoothing algorithms for mean-flow extraction in large-eddy simulation of complex turbulent flows”, Physics of Fluids 1 December 2010; 22 (12): 125104, doi:10.1063/1.3490063