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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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reproducible research, collaboration, and knowledge sharing. You should meet the following qualifications: A PhD in Electrical Engineering, Robotics, Computer Science, Artificial Intelligence, or a closely
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for increased public health and implementation of new health knowledge and technologies. Currently, our department has approximately 280 employees, 100 Ph.D.-students enrolled in the Doctoral School in Medicine
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exist. To address this knowledge gap, in the BUG-ID consortium, seven European universities, one research institute, one hospital and six private companies have teamed up. Our consortium will train 15
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environment used in APEX (sectoral simulators and/or their ML metamodels), with support from the team. Formulate the policy-learning problem, including state/action representations, reward design (with
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and UUV to support autonomous coordination and mission execution. This includes using relative measurements, shared environmental representations, and synchronized data exchange to enable precise and
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measurements, shared environmental representations, and synchronized data exchange to enable precise and reliable positioning across vehicles. Multi-sensor integration: Designing sensor fusion pipelines