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technologies for remote detection. Specifically, this position involves research on generation of widely tunable GHz-THz femtosecond pulse bursts to optimize laser-matter coupling, plasma generation, and
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to optimize workflows and procedures. Profile We are seeking a highly motivated, efficient, energetic and optimistic senior bioinformatician at postdoc level, with a strong interest in aging and
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, graph theory, graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and supported by the COMMLab, the 6GSPACE Lab, the HybridNetLab, the QCILab
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understanding with applied research and close collaboration with industrial partners, we develop solutions that contribute directly to the optimization of industrial-scale electrolyzers. More information about
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researcher, your responsibilities will include: Optimizing, and running head-fixed mouse behavioural tasks for harm-aversion and self-fear. Acquiring and analysing functional ultrasound imaging data from ACC
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experimental PhDs and Canon Production Printing to enable data-driven ink optimization. Why Join? Work in the multidisciplinary Processing and Performance of Materials group Work at the forefront of sustainable
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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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into value-added products Design, build, and optimize plasma reactors and related experimental systems. Conduct thermodynamic and kinetic analyses of plasma-driven chemical processes. Perform chemical and
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to work on the design of novel nucleic acid delivery technologies for ex vivo/in vivo CAR-T cell engineering. The postdoc will assist in the development, optimization, characterization and (ex vivo/in vivo
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 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