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eco-friendly sensor technologies, favoring collaborations between local industrials and academia and building innovations between local actors to create startups on disruptive technologies. Within
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- Design pilot and data collection of MEEG and behavioral experiments with Psychtoolbox, JsPsych, Pavlovia - Univarate and multivariete analysis (RSA, encoding and decoding models) of MEEG data at sensor and
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for the High-Luminosity LHC. Our primary responsibility is the integration of double-sided silicon sensors onto mechanical support structures (ladders), including the associated electrical, optical, and cooling
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, robustness under varying turbulence, and autonomy for distributed systems. To address this, the group integrates Artificial Intelligence into AO control loops, using deep learning to handle sensor
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-criteria, defining their formalization as fuzzy subsets, and characterizing their uncertainty; Integrating Machine Learning algorithms to better account for low-level sensor data (precipitation, wind-driven
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analysis for more geometries and with a reduced number of sensors - Implementation of the MSE method on a cylindrical structure immersed in water and sensitivity analysis - Algorithmic and experimental
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) * electromagnetic design of device using soft-ware such as comsol *clean room fabrication using both optical and e beam lithography *Optoelectronic characterization of infrared sensor (I-V, photocurrent spectrum
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sensors, such as the Underwater Vision Profiler or the ZooScan, as well as an increase number of software packages to process and control the quality of the data generated by the instruments, sort images
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-effectively integrated into advanced technology nodes for sensor, nonvolatile memory, logic, and neuromorphic applications. Currently, hafnium-zirconium mixed oxide (HfxZr1-xO2) offers the widest stoichiometry