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Description Are you curious how Deep Learning and Online Learning can be effectively combined to create new learning paradigms? Job description Online learning algorithms achieve robustness often at the expense
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) Group at the Faculty of Computer Science. Led by Prof. Dr. Martin Pawelczyk, who recently joined the University of Vienna from Harvard University, our research sits at the intersection of AI Safety and
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of Computer Science. Led by Prof. Dr. Martin Pawelczyk, who recently joined the University of Vienna from Harvard University, our research sits at the intersection of AI Safety and Data-Centric AI. We aim to make large
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PhD Studentship: Quantum Algorithms for Nuclear Level Densities Atomic nuclei have a rich structure, with heavy nuclei having many excited states – of order thousands or higher. Knowledge
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of Computer Science. Led by Prof. Dr. Martin Pawelczyk, who recently joined the University of Vienna from Harvard University, our research sits at the intersection of AI Safety and Data-Centric AI. We aim to make large
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), such as solar photovoltaics (PV), electric vehicles, heat pumps, and storage systems, into distribution networks. Delivering this transition requires coordinated innovation across both active distribution
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unpredictable, standard foundation models often output overconfident, flawed embeddings when faced with unprecedented climate anomalies. To solve this, you will also develop rigorous Out-of-Distribution (OOD
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skills and fosters employment opportunities in the field of cultural and environmental heritage at both national and international levels. Main supervisor(s): Dr Clotilde Boust (C2RMF & CNRS-SATIE) Prof
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scenario; Develop a novel self-calibrating, heterogeneous distributed platform capable of providing the necessary sensing, transport, compute and data aggregation capabilities on demand. Consider how partial
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Experienced researcher position. Part-time 40 hours/month distributed unequally, gross hourly salary of 240 lei, fixed period until June 30, 2026. The project is entitled “A Study of Consumer Trust in Online