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derivatives to bio-chemicals on the anode side and simultaneously to generate green hydrogen in the cathode side. Subject description Energy engineering concerns the development of technologies and processes in
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | 21 days ago
. PhD Topic AI-based real-time embedded audio Digital Signal Processing (DSP) is an emerging field which promises to revolutionize our daily life. Embedded real-time audio DSP can be found in hearing aids
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parallel, you will uncover the mechanisms that control localized and cell-type-specific translation, and how these change across developmental stages or within subcellular compartments. During your PhD, you
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overview of translational regulation during development. In parallel, you will uncover the mechanisms that control localized and cell-type-specific translation, and how these change across developmental
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algorithms for application parallelization, simulators and virtual platforms for application- and architecture exploration, hardware/software co-design and operating/runtime systems. Typical application
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22 Aug 2025 Job Information Organisation/Company Delft University of Technology Research Field Engineering » Process engineering Researcher Profile First Stage Researcher (R1) Positions PhD
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diffusion techniques to design materials with targeted optical properties, scaling to large systems through efficient representations and GPU parallelization. We will also create multi-fidelity predictive
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knowledge and tools to equip local decisionmakers to better deal with conflicting values in parallel transitions and requires an interest in both theory development and engagement with practice. The PhD
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information through parallel channels—manual signs, spatial grammar, facial expressions—operating simultaneously in 3D space, presenting unique computational challenges for cross-modal alignment. The project
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image sequences. As a benchmark, end-to-end deep learning models will be developed using raw image data. In parallel, shallow learning models (e.g., Gaussian processes) will be explored based on insights