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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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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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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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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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spontaneous orbital ferromagnetism. The research will combine advanced sample fabrication, optimization of magnetic sensors, and low-temperature, low-noise measurements of the transport and magnetic properties
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Postdoctoral researcher (M/F). Modeling damage during earthquakes. Comparison with geophysical data.
work will consist of optimizing the codes that generate input data and process output data. • The postdoctoral researcher will carry out comparative work using data from geodesy and seismology