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Two DTU Tenure Track Assistant Professors in Autonomous Modelling and in Robotic Synthesis of Ene...
and robotics. As the successful candidate, you will develop innovative research programs spanning atomistic and mesoscopic materials simulations, machine learning, foundation and surrogate models
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(satellites, drones, etc.) through AI and machine learning; 3) validation and feasibility of the introduced technologies through full-scale pilot scale, demonstration, documentation, and simulations
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) the application of remote sensing (satellites, drones, etc.) through AI and machine learning; 3) validation and feasibility of the introduced technologies through full-scale pilot scale, demonstration
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logical way and parametric simulation engines. Familiarity of machine learning / AI techniques and custom LLMs generation is beneficial. Knowledge of life cycle assessment (LCA) and LCA methods, carbon
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, statistics, physics or relevant fields. Strong background in machine learning, preferably experience in probabilistic modeling, Bayesian machine learning, or graph representation learning. Programming skills
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framework for understanding emergent deception in human-AI interaction by uniting behavioural-psychological, economic-strategic, and machine learning perspectives. The postdoc will be jointly supervised by
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degree in computer science, mathematics, statistics, physics or relevant fields. Strong background in machine learning, preferably experience in probabilistic modeling, Bayesian machine learning, or graph
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of bioacoustic signals. Extensive experience with programming (Matlab, R, Python) including GPU programming is required, and familiarity with edge-based machine learning (particularly sound event detection), open
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industrial energy systems that combine physics and data to become adaptive, autonomous and trustworthy? To get there, you will work at the intersection of thermal energy systems, machine learning and
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the Machine Learning, Artificial Intelligence, or Robotics, reflected through contributions to major conferences (ICLR, IEEE ICRA, NeurIPS, ICML, CVPR, ECCV, SIGGRAPH, ICCV, etc.) Solid mathematical and