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embodied AI agents can dynamically adapt to group behaviors and learning needs The project will combine observational studies, interaction design, and experimental evaluations to develop embodied AI-driven
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array antenna systems for imaging MIMO radar in autonomous driving applications. This work will advance the design and characterization of intelligent devices and environments for wireless communications
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(and the willingness to learn more), with an interest in biological/ecological questions; Experience with programming or the willingness to learn to program (the lab relies mostly on R and C++, but
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totaling 60 ECTS credits) and join an international research team with backgrounds in sociology, political science, network science, statistics, and machine learning. More information on the PhD program can
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application! Your work assignments Our research projects focus on distributed sensing, hardware-efficient signal processing, robustness and resilience, and communication-efficient decentralized machine learning
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approach that integrates wireless communication, computer vision, and machine learning to optimize PC transmission from sensors to an edge server for remote registration. The research is funded by Wallenberg
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on: analytical chemistry methods for organic matter characterization and pollutants measurements are highly merited. designing and performing laboratory studies are highly merited operating and monitoring
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if you have worked with prediction models, machine learning or AI models and are familiar with blood cells such as neutrophils, leukocytes and platelets. Work experience in the area is meritorious. If you
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of this WASP-financed project is machine learning, in particular dealing with generative models and instabilities associated with cycles of retraining on mixtures of human and machine-generated data
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and computational methods within quantum mechanics and statistical physics with the aim to design alloys for rare-earth-free high-performance permanent magnets. You will use computational techniques