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Sadron Institute. The team works on themes related to the process-structure-property correlations of pi-conjugated materials for applications in organic electronics. The SYCOMMOR team has particular
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using the KM3NeT detectors • Data analysis from SVOM instruments as well as images from the COLIBRI telescope • Participation in KM3NeT shifts and service tasks (calibration, construction, processing), as
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an internationally recognized research team at LAAS-CNRS in Toulouse, focused on developing autonomous mobile machines that integrate perception, reasoning, learning, action, and reaction capabilities
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correlations or more innovative methods of multivariate analysis and we anticipate here an opportunity of using machine learning that could help in predicting properties or classifying sources. A last step will
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: electronic structure calculations (plane wave DFT if possible), statistical thermodynamics, molecular dynamics. Skills in Python, bash scripting, Fortran 90 and machine-learning would be appreciated. The PIIM
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for such applications. To respond to these challenges, this project aims to investigate automated decision making based on machine learning. The candidate (H/F) will propose and validate centralized as
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to the problem of thermal measurement at the nanoscale. This thesis is part of the ANTICHI (Advanced Nanoscale Thermal Imaging and CHaracterization Instruments) project, which aims to provide a versatile
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fundamental understanding of climate change and its impacts, extending to the development of prototype climate services co-designed by stakeholders and climate modeling experts. The goal is to accelerate
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-Performance Computing for Exascale" contributes to the design and development of numerical methods and software components that will equip future European Exascale and post-Exascale machines. This program is
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of front-end electronics and miniature RF antennas for chronic implantation. You will prototype and characterize the wireless link (power + sensing), design and optimize sensor-resonator coupling, and