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expanding its focus to space-based missions. We are contributing to the High Energy cosmic-Radiation Detection (HERD) experiment, a next-generation detector for the Chinese Space Station. In parallel, we
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Infrastructure (SBDI) and maintains the Swedish Species Observation System. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes
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anesthesiology, diagnostic imaging, animal nursing, epidemiology, laboratory animal medicine, surgery, clinical pathology, medicine, and domestic animal reproduction. In addition, the SLU University Animal
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or exceeds these requirements while expeditiously furthering the research objectives of the Department of Dermatology. This position must be able to work independently on multiple research projects in parallel
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. Integrate the feed chemistry data being developed in a parallel project. Travel to India to help implement the updated model. This would be as needed and no more than two times per year. Conduct a comparative
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components, integration into a wearable format, and establishing a consistent build, test, and quality-check process so that multiple units can be manufactured with comparable performance. In parallel
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algorithms for parallel/distributed AI/ML Hardware-aware and resource-efficient partitioning for parallel/distributed AI/ML Optimization of process-to-process communication in parallel/distributed AI/ML
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other labs will be developed for comparison with other techniques and computer IRIS Lab for analyses of the 3D mapping by IA models References [1] A. Kiełbasa, K. Kowalczyk, K. Chajec-Gierczak, J. Bała
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 28 days ago
. - COMPETE2030-FEDER-00731800, Operation No. 16163, funded by COMPETE2030 and national funds (FCT) under Notice no. MPr-2023-12. Host Institution: i3S - Instituto de Investigação e Inovação em Saúde, Porto
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will play a key role in building a parallelized, agent-driven exploration system and integrating a multimodal detection pipeline, ensuring real-time performance, scalability, and deployment readiness in