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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | 3 days ago
deep understanding of Electrical Engineering fundamentals (voltage, current, reference circuits, amplifiers, noise, power, design tradeoffs, electricity & magnetism, microelectronic design, etc.) Some
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No. 101227010 , at DTU Electro, the Technical University of Denmark, we are seeking a candidate for a PhD position to research novel noise characterization techniques for SiC optical frequency combs targeting
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about the vibrational (phonon) dynamics of a molecule’s interactions with its environment [2]. We will extend this to, e.g., complex molecules, ultimately seeking to identify photonic signatures of non
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-Curie Grant Agreement No. 101227010, at DTU Electro, the Technical University of Denmark, we are seeking a candidate for a PhD position to research novel noise characterization techniques for SiC optical
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-layer repulsion and steer ligand–receptor encounters on demand. Track 2 — Acoustic actuation in nanogaps: Use high-frequency out-of-plane vibrations to generate squeeze-film pressures and acoustic
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, curriculum over geometry/BCs, calibration of predictive uncertainty, and robustness to sensor noise. Tasks: forward prediction (temperature fields), inverse reconstruction (defect size, depth, orientation
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preliminary identification of marine species potentially affected by noise exposure. Keywords: Environmental seismology, acoustics, bioacoustics, machine learning, data processing We seek a motivated doctoral
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impairments arising from practical limitations in CV-QKD systems (e.g., bandwidth constraints, ADC resolution, phase noise etc). Emphasis will be placed on energy-efficient, low-complexity hardware solutions
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Hilbert spaces, higher information rates, enhanced security, and increased robustness to noise. This project aims to advance high-dimensional quantum information both fundamentally and experimentally
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uncertainty, modality dropout, and noise propagation, which can degrade robustness and erode trust in model outcomes. This project aims to create a unified framework for building lightweight, data-efficient