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advanced machine learning models and physics-informed algorithms for analyzing high-speed XRD data, with a focus on identifying critical transformation windows and assessing phase evolution kinetics
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 2 months ago
6 Mar 2026 Job Information Organisation/Company Inria, the French national research institute for the digital sciences Research Field Computer science Researcher Profile Recognised Researcher (R2
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Framework Programme? Other EU programme Reference Number 2026/73 Is the Job related to staff position within a Research Infrastructure? No Offer Description THE BIOMEDICAL RESEARCH INSTITUTE OF MÁLAGA NEEDS
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these capabilities. The RA will continue and expand the work on this topic to further improve the semantic SLAM algorithms, to improve their performance and robustness and to allow their computation on edge devices
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multidisciplinary team specializing in medical imaging and algorithm development. Our work focuses on advancing the use of computer vision, deep learning, and machine learning for analyzing medical imaging modalities
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COTS frames (DJI, Holybro, etc.) via companion computers. Swarm Robotics: Familiarity with consensus algorithms, formation control, and communication protocols for multi-agent systems. Security
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, Computer Science, Statistics, or other related fields. Familiarity with machine learning and signal processing algorithms for wireless communications. Good written and oral communication skills
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of novel federated causal inference algorithms and associated software APIs. Validation of algorithms via simulations and live demonstrations. Job Requirements A Master's degree or higher in Computer
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Laboratory of Atmospheric Optics is offering a 3- to 6
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of Computation Group, seeks applicants for a postdoctoral fellowship to conduct research in differentially private learning, its connections to replicability of algorithms, and algorithmic fairness. Basic