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Field
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learning, and generative AI Design and implement algorithms for quantum-inspired and quantum-enhanced generative models Investigate theoretical foundations of tensor networks, entanglement, and collapse
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particle (SEP) events. The project is a joint collaboration of Algorithmics and Computational Intelligence research group at the Department of Computing and Space Research Laboratory at the Department
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. The projects will also focus on applications and algorithms employing X-ray scattering models to uncover spatiotemporal correlations in ultrafast phenomena, particularly fluid dynamics, studied at the recently
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 3 hours ago
dedicated Engineers responsible for the actual implementations. Hence, your primary focus will be on the creation of sound algorithms and methods, ensuring their theoretical integrity and applicability
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project is to develop a high-performance computing framework for mass spectrometry proteomics to enhance efficient processing and interpretation of large datasets using deep learning algorithms and GPU
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· Carry out research activities under the Department's contracts in the RS2M field · Participate in and ensure the delivery of project deliverables · Design and develop models, algorithms, and
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learning, and AI-driven manipulation. This position offers the opportunity to work on real-world robotic systems and develop novel algorithms at the intersection of robot learning, control, and AI
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networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models Statistical learning theory and complexity analysis
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scale. Test methods for calibration corrections and noise reduction in retrieved data. Test algorithms for retrieval of sea surface temperatures from infrared radiances. Test algorithms for cloud masking
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algorithms (convex/nonconvex, stochastic/robust, MPC) for real-time dispatch, frequency regulation, and DER coordination. Integrate data-driven and physics-informed approaches for state estimation, forecasting