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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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. 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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. 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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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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design of soft scaffolds and synthesis using extrusion-based bioprinting. Experimental characterization and constitutive modeling. Compression experiments on 3D-printed scaffolds under different conditions