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, CeRh2Si2, TbB4 etc.) near metamagnetic transitions and unconventional superconducting phases. Within step 1, magnetization probes will be developed, tested and compared before choosing the most optimal
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experimental trials on metal additive manufacturing processes - Ability to design and execute experimental plans (DoE) for process investigation and optimization - Ability to acquire, process, and analyze
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numerical techniques to study collective states in active matter. Depending on the candidate's profile and interests, the research can involve various aspects of the modeling and the optimal control of active
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to the lab's research aimed at understanding how polyploid cells regulate their optimal size while maintaining their function. This effort is part of the lab's broader project to study ploidy transitions
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of mathematical modeling, with a particular focus on stochastic modeling, optimization and more recently machine learning. Indeed, over the last years, the team’s activity has been marked by a strong shift toward
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and 3D finite element modelling (COMSOL, CST) of the optical control process for materials. -Integration of the optimal compositions into simple test structures to directly evaluate electrical switching
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, and optimizing cleanroom-based micro- and nanofabrication processes dedicated to the fabrication of these MEAs; Integrating the developed bioelectronic devices into microfluidic organ-on-chip platforms
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identify the optimal foaming process parameters and study the effects of additives such as starch, silica and calcium carbonate on thermal, mechanical and water-related properties. They will also be
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participate in the design, fabrication, and optimization of van der Waals heterostructures and related electronic devices. The work will involve micro- and nanofabrication techniques as well as the assembly
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 2 months ago
these limitations. By leveraging RL during the post-training phase, foundation T2V models can be explicitly optimized to follow complex conditioning signals, enforce temporal consistency, and align with specific