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• Develop, consolidate, and optimize fMRI and EEG neurofeedback algorithms. • Design, integrate, and test standalone neurofeedback software (software suites for clinical environments). • Contribute
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, so that it can be easily used in practice (fast optimization, embedded decision-making, online updating). 1. Design a lightweight statistical/probabilistic surrogate model, integrating: • an estimation
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to optimize their durability and efficiency under industrial conditions. The goal is to contribute to a sustainable energy storage solution while avoiding the use of expensive metals. The postdoctoral
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of the work is to advance and automate the use of ptychography on various sample types. In particular : 1) accelerate the reconstruction process using a multislice algorithm 2) allow a 3D reconstruction and 3
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the hypothesis that the plant (WP1), bacterial community (WP2), soil organomineral association (WP3) continuum can, while meeting agronomic requirements (WP4), be optimized to increase soil carbon sequestration
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obtained by MOCVD deposition. A PhD student at LMGP is currently developing and optimizing the operating conditions to control nanowire geometry, network density and connectivity, and coverage. The recruited
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at international conferences. Development and optimization of experimental protocols: stereotactic injections, optogenetics, chemogenetics, in vivo imaging (fiber photometry, calcium imaging). • Development and
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and optimize TD-RAS (time-dependent restricted-active-space) methods for many-body systems including positrons. - Carry out large-scale numerical simulations of photoionization and de-excitation
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(MERCE). The main objective is to develop safe planning and reinforcement learning algorithms with various degrees of confidence for variants of Markov decision processes. More precisely, we will develop
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layer to accommodate lattice mismatch while enabling the active use of Si as a bottom cell. The applicant will be involved in the deposition and optimization of the GaAs, its doping, passivation/contact