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, led by Orange Labs, whose objective is to design and implement efficient algorithms for computing optimal solutions in order to recommend the best actions a telecommunication operator can undertake for
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optoelectronic materials through advanced characterization and AI-guided optimization of epitaxial growth parameters. The PhD student will work on the various technological building blocks of the epitaxial growth
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silicon waveguides with a nanometric core. This work will include the development and optimization of simulation tools for the design of these waveguides, combining numerical results with simplified models
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measurements, to understand and to optimize their performance, in particular by taking into account new data measurement from real-life devices. Skills For this position, you should meet the following
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approaches to avoid costly design and fabrication cycles for the optimization of these circuits are possible, in particular the use of Look-Up-Table (LUT)-based techniques that exploit the characterization
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in various fields, including petrochemistry, environmental science, polymers, and biomass valorization. The selected candidate will work closely with researchers and PhD students at the laboratory, as
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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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for their functions in PDE, or co-precipitation with known PDE factors, which could not recover transient and/or unstable interactors. To overcome these limitations, this project aims to a) optimize Cas13-based gene
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, optimization, dynamic systems, decision theory, Bayesian inference) ● Is motivated to apply these methods to ecological, evolutionary, and conservation systems; ● Is comfortable with uncertainty, modeling
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hybrid systems combining DES and conventional extractants with a view to achieving synergies in terms of efficiency. • Optimize operating conditions (ultrasound, microwave activation) to improve