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collaboration. Qualifications: Applicants must have a PhD in Robotics, Control Engineering, Machine Learning, AI, Mechanical or Electrical Engineering, or a closely related field. Strong focus on robot
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in continual learning settings. The core focus is on leveraging Reinforcement Learning (RL) to make the training and deployment of LLMs more computationally and sample efficient. This approach aims
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continuous corrections during execution, and where learnings from prior actions performed on the same product or component are also leveraged.With the ambition to boost process adaptability, while assuring
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subsea digital twin of deep-water mooring lines for floating offshore wind turbines. The digital twin will be integrated with machine learning algorithms for detection of primary entanglement due
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functions to work properly. Please turn on JavaScript in your browser and try again. UiO/Anders Lien 2nd February 2026 Languages English English English PhD-/Postdoctoral Research Fellowship "Convergence and
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scientific curiosity. You thrive at the boundary of robot learning, computer vision, deep learning, and simulation, and you are excited to see your research running on real robots. You communicate clearly
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novel machine learning models—including Physics-Informed Neural Networks (PINNs), variational autoencoders, and geometric deep learning—to fuse multimodal data from diverse experimental probes like Bragg
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 26 days ago
position will include, but is not limited to, multimodal+embodied semantics, human-like language generation and Q&A/dialogue, and interpretable and generalizable deep learning. The duties of the postdoctoral
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. For the project The Role of the Ocean in Earth System Stability PIK’s Research Department 1 Earth System Analysis, is offering a Scientific Position (PhD or Postdoctoral level) (m/f/d) (Position number: 03-2026
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on a unique cohort of 1,750 human liver samples and 400 blood samples and integrates high-resolution genomic approaches (ultra-deep WES, ddPCR, single-cell RNA-seq, spatial transcriptomics). Main