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). Expected results: • New HWCVD technology validation and optimization. • Obtain high optical performance a-SiC thin films (test material in small dimension, <2-inch) to be used in other WPs. • Comprehensive
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of electrochemical reactions carried out under strong, controlled magnetic fields. Part of the work will involve establishing an in-situ characterisation method, supplemented by research into optimal experimental
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foundations and principles of Machine Learning, Linear Algebra (vectorial and matricial operations, optimization), with a particular focus on Neural Networks (pytorch), 3) problem solving skills, 4) familiarity
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Louis Lions. - Design and implement innovative methods for the numerical solution of wave propagation problems within the FreeFEM software, using high-performance computing - Optimize the code
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in a strongly heterogeneous setting (e.g., CPUs+GPUs). Additionally, this work can benefit from the developments of WP1 and WP2 of Exa-SofT around the development of optimization techniques
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an assessment framework that will enable us to better identify and propose, in a transparent manner, management measures for optimal sustainability, tailored to each study area and applicable to different sites
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validated at CPPM. In parallel, the candidate will improve data reconstruction algorithms by using artificial intelligence techniques (e.g. neural networks), to optimize the separation between signal and
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and optimize their properties for neuromorphic computing through combined electrical and MOKE measurements, and train them to achieve artificial intelligence tasks. - Micromagnetic simulations - machine
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to several aspects of the project, including: -design, development and validation of experimental optical microscopy setups -modelling and optimization of experimental parameters -adaptation and further
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of sea turtles - Developing innovative machine learning methods to analyze the sounds associated with these behaviors - Automating the processing of audio and visual data to optimize the quantity and