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-21-CE08-007 ended in March 2025). The work in N POLAR will focus on the development and optimization of this innovative process (hybrid semiconductor/metal/semiconductor heterostructures) in order to
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conduct in vivo experiments to investigate retinal neurovascular dynamics using the AO-RSO system; Develop or adapt high-speed image acquisition and processing methods for simultaneous measurement
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optics experiments will contribute to a better understanding of local annealing processes, with the goal of achieving optimized control over the final material state, taking into account its crystalline
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proximal and remote sensing technologies with AI based decision support systems to optimize water, nutrient and fruit growth/maturation management and ultimately improve olive production efficiency and
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research. Key Responsibilities: Develop and run a Cu–Cu hybrid bonding flow for fine-pitch 3D integration. Optimize process windows (pressure/temperature/anneal/surface activation) to minimize contact
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multi-layer systems using a strip casting process. The project is divided into 2 tasks, as follows: 1) Development of an optimum casting formulation based on the starting powder supplied. Optimization
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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | 28 days ago
equipment, etc.) Social, cultural and sports events and activities Access to vocational training Social security coverage Selection process Website for additional job details https://jobs.inria.fr/public
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23 Dec 2025 Job Information Organisation/Company University of Siegen Research Field Computer science » Computer architecture Researcher Profile First Stage Researcher (R1) Positions PhD Positions
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Deadline : April 15th 2026 · Selection Process : Mai 2026 · PhD Start Date : September-October 2026 How to apply All information are provided on the website of the project : https://www.eu4greenfielddata.eu/
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processing and for large-scale cohort studies. Key Responsibilities: Manage and optimize the sample management process, ensuring efficient workflow for high-throughput studies. Ensure optimal performance