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in making a difference by bringing innovation to government organizations and beyond? Apply to join our team. Overview: As a Senior Machine Learning Research Scientist, you will specialize in
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this project, you will develop the next generation of federated machine unlearning algorithms—methods that can efficiently deliver genuine, verifiable, and robust erasure without sacrificing model performance
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computer vision. Unlike traditional engineering research roles, this position functions as a specialized Research Software Architect, bridging the gap between photogrammetry and modern generative AI
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thesis lies in linking the market perspective with the grid perspective. Based on this, suitable modeling and integration approaches shall be explored in order to analyze different ways of considering grid
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, modulation classification, sensing, and adaptive spectrum optimization in diverse operational environments. Your work will focus on modeling and algorithmic aspects related to the development of highly
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between the brain signals of different subjects. The aim of this project is developing new adaptive and machine learning algorithms to successfully decode brain signals across subjects. The prospective
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isolation algorithms and data-driven classifiers. As postdoc, you will principally carry out research. You are expected to actively publish and present results in scientific journals and conferences. A
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advanced mathematical algorithms and AI frameworks for modeling and optimizing power electronic components and systems. To support our team, we are looking for a working student (all genders) in the field
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on understanding how different excitation methods generate polarons and correlated materials in the cuprates and other quantum materials, building on our recent results in the vanadium dioxide (see Johnson et al
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performance should improve over time as more data becomes available. The diagnostic conclusions will be presented to an operator using a combination of AI-based fault isolation algorithms and data-driven