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works have shown that for embedding hierarchies, we should abandon Euclidean geometry altogether and operate in hyperbolic space [1]. Our lab has published multiple papers showing that hyperbolic deep
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systems strong analytical and problem-solving skills fluency in English, both written and spoken Not required, but helpful: Experience with biomedical data/algorithms An affinity for applications
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Not required, but helpful: Experience with biomedical data/algorithms An affinity for applications of technology Contributions to open source projects This is what we offer A temporary contract for 38
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geometry altogether and operate in hyperbolic space. Our lab has published multiple papers showing that hyperbolic deep learning has strong potential for computer vision, from hyperbolic image segmentation
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, boosted by AI-data augmentation for extrapolating spectrum patterns from multiple sources. To design a scalable computing framework using a physics-informed neural network for distributed spectrum analysis
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designed to meet multiple needs in marine biodiversity monitoring. The project aims to develop embedded novel deep learning and computer vision algorithms to extend the system’s capabilities to classify
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for machine learning, with research topics ranging from decentralized and federated optimization, adaptive stochastic algorithms, and generalization in deep learning, to robustness, privacy, and security
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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that may empower consumers to resist persuasion and reduce harmful consequences? Are you passionate about advertising, algorithms and social media? Then apply for this PhD project focused on demystifying
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, algorithms and social media? Then apply for this PhD project focused on demystifying algorithmic persuasion by commercial advertisers on TikTok from a differential vulnerability perspective. Who is vulnerable