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) To develop Deep Learning algorithms to significantly speed up probabilistic inference algorithms of current spatial birth-death models 2) To incorporate fossil stratigraphic and spatial information into a new
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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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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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influence helps detect labeling errors or prioritize unlabeled images, optimizing the learning algorithm and service quality. The doctoral student will carry out their work at IMAG (UMR of Mathematics) and
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agents and as photosensitizers. The PhD student will acquire expertise in techniques for studying ROS generation in solution (indirect methods using internal dyes) and in vitro (using ROS-active dyes
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nonlinear optics). The PhD student will acquire expertise in the field of water-soluble chiral nanoclusters, from individual nanoclusters to supramolecular nanoclusters, focusing on their photophysical
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, teamwork • Ability to respond to challenges • Dealing with confidentiality • Efficiency with office software /Behavioral skills : • Self-learning and interpersonal skills • Excellent communication skills
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will explore if learning and memory paradigms trigger the recruitment of RNAs to specific synaptic compartments. Second, the student will study the cellular machineries involved in local RNA recruitment
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parameters to identify regimes that ensure both flame stability and low pollutant emissions. Machine learning techniques have recently shown promise for Design of Experiments (DoE) and interpretation of large
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with both the CNRS and UGA, organized into five research teams conducting work in cognitive science (Body and Space, Development and Learning, Language, Consciousness, Memory & Metacognition, Vision