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– Adaptive & Agentic AI. The PhD project focuses on developing robust and reliable machine learning systems that can adapt at test time under real-world distribution shifts. Modern foundation models (e.g
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mathematical modelling and simulation. Partial differential equations will be applied to model drug distribution and partitioning in multiphase systems using the drug’s partition coefficient as a driving force
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of microbes. Degradation of organic carbon in deep sea sediments is critical for marine carbon cycling and climate regulation but difficult to quantify. This project will investigate the distribution
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Reference no.: 5509 The employment duration is 3 years. Initially limited to 1.5 years, the employment relationship is automatically extended to 3 years if the employer does not terminate it within the first
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systems Experience in deep learning, computer vision, or multimodal data integration Exposure to federated learning, privacy preserving analytics, or distributed systems Knowledge of clinical data models
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- Quantum Reinforcement Learning, quantum computing, QKD - quantum key distribution, entanglement distribution System-level design and optimization AI & Intelligence: Agentic AI, Edge AI, information
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learning Distributed and federated training The candidate is expected to hold a relevant MSc degree in Computer Science, Data Science, Physics, (Applied) Mathematics, Computational Statistics or another
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Senior Researcher in Ecosystem based marine management, nature restoration, and anthropogenic imp...
We are seeking a senior researcher that is expected to work maximum 10 hours per week and with experience within the research areas anthropogenic impacts on ecosystems and ecosystem-based management
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, the sustainable use of the world's coastal systems and the resource-compatible enhancement of the quality of life. From fundamental research to practical applications, the interdisciplinary research spectrum covers
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About us The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character. The Interdisciplinary Centre for Security, Reliability