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of viral populations across oral samples. The successful candidate will have previous experience implementing and optimizing viral metagenomic analysis pipelines and working with commonly used command-line
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Innovator Grant from the Novo Nordisk Foundation and carried out under the supervision of Professor Claus Elsborg Olesen. The project’s main objective is to optimize the RNA delivery platform through in vitro
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engineer to significantly redesign it and build the next generation of the OpenML platform. Key publication: What you will do Goals and core tasks: Optimize accessibility for all experience levels via
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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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waste management pathways. The research will support process optimization and scale-up by assessing different feedstocks, operating conditions, and valorization routes for syngas and recovered materials
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of the hamstrings during push-off can enhance gait after stroke. This position builds on those findings: you will adapt an existing FES shorts system for stroke rehabilitation, test and optimize it with patients
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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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system for stroke rehabilitation, test and optimize it with patients, retrain the stimulation-control algorithm for stroke-specific gait, and evaluate usability, comfort, and fit during prolonged use. You
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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 | 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