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At the Fraunhofer Institute for Laser Technology ILT, we may not be developing lightsabers to fight the dark side of the force, but our innovationsoften sound like something out of science fiction
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SHARE@NTU Lab is developing key technologies for humanoid robot research, designed for intelligent service, industrial assistance, and human-centric environments. The key technologies include
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algorithms for information gathering problems involving one or more rational autonomous agents. The objectives include: the development of learning algorithms; the study of their theoretical properties
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algorithms for problems related to information markets involving multiple rational autonomous agents. The objectives include: the development of learning algorithms; the study of their theoretical properties
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advanced machine learning models and physics-informed algorithms for analyzing high-speed XRD data, with a focus on identifying critical transformation windows and assessing phase evolution kinetics
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, but this option can be time consuming and unsafe when testing complex algorithms (navigation, grasping . . . ). Using a simulator can speed up development, is safe, but breaks the natural interaction
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you will do Driving innovative AI research through the development and implementation, practical application, theoretical analysis and evaluation of AI algorithms Use of XAI tools to explain machine
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Federated learning (FL) is an emerging machine learning paradium to enable distributed clients (e.g., mobile devices) to jointly train a machine learning model without pooling their raw data into a
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Student (f/m/d) in Quantum Algorithms for Droplet and Bubble Oscillation Dynamics Modelling. Your tasks Development and implementation of numerical and algorithmic methods for the simulation of fluid
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the LLM effectiveness. Key Responsibilities: Research and develop novel ML-based methodologies and algorithms for multilingual and multimodal LLMs. Working closely with other Postdoc/RA/PhD students