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Are you passionate about compression, analytics, and machine learning for the Internet of Things and can you contribute to the development, operation and support in cutting-edge projects in strong
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engineering to identify variants with high performance towards PFAS degradation. Enzyme immobilization for efficient and continuous enzymatic PFAS degradation in realistic water matrices and under water
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. An extension of 1–2 additional years may be offered, subject to satisfactory performance. Job description The successful candidate will contribute to cutting-edge research on topics including: Token compression
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effects of exposure, biomonitoring and advising national and international authorities. The analytical chemistry laboratory measures concentrations of drugs or environmental chemicals in various matrices
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engineering to identify variants with high performance towards PFAS degradation. Enzyme immobilization for efficient and continuous enzymatic PFAS degradation in realistic water matrices and under water
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and interpretability, analogous to RAG (Retrieval-Augmented Generation) in LLMs Investigating methods for improving AI model sustainability, e.g. model compression techniques (such as quantization and
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statistics This PhD project falls under the collaboration between Research Thrust RT2 Physics-based models, and Research Thrust RT3 on representation, compression, learning, and inference. For long-distance
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useful for production of fermented foods, especially in plant-based alternative and hybrid food matrices. Design and conduct studies on lactic acid bacteria for fermentation performance, biopreservation
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international authorities. The analytical chemistry laboratory analyzes concentrations of drugs or environmental chemicals in various matrices. The project In the translational group, we are looking for a postdoc
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candidate will be affiliated with the Stochastic Analysis in Aarhus project, led by Professor Fabrice Baudoin and funded by the Villum Foundation. The group conducts research in areas such as random matrices