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Field
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agentic AI (e.g., large language models, algorithmic systems) shape users’ psychological and behavioral well-being, particularly among vulnerable populations. Applicants are encouraged to approach
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3D environments. • Design of a robust control architecture to ensure autonomous navigation using information from the optical localization system (development of estimation algorithms, use of observers
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distributed wireless systems" which is conducted in collaboration between Linköping University (LiU) and Lund University (LU). Read more here: https://elliit.se/project/machine-learning-for-sensing-in
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conducted in collaboration between Linköping University (LiU) and Lund University (LU). Read more here: https://elliit.se/project/machine-learning-for-sensing-in-distributed-wireless-systems/ Distributed MIMO
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training datasets; Design and carry out laboratory experiments to produce representative experimental training data; Develop physics-informed machine learning algorithms, trained on both numerical
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-related traits, and heterosis. In the era of large population size and dense genomic data such as whole-genome sequencing, new algorithms are needed to remove the bottleneck of computational load for such a
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usage, memory and storage demands, and associated carbon emissions while aiming to maintain model quality. Your work will include developing new methodologies and algorithms for resource-efficient
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laboratory. Where to apply Website https://networks.imdea.org/job/phd-position-in-ai-enhanced-secure-6g-services/ Requirements Research FieldEngineering » Communication engineeringEducation LevelMaster Degree
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for a Research Assistant Professor position. We seek candidates whose research examines how increasingly agentic AI (e.g., large language models, algorithmic systems) shape users’ psychological and
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of approaching reconstruction and variability analysis. The project combines applied mathematics, computational imaging, and structural biology. You will develop algorithms, implement and test software tools, and