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company, where you’ll take wind farm design and simulation tools to the next level. By fusing cutting-edge physics-based modeling with rapid, data-driven engineering, you’ll develop innovative solutions
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. Experience with simulation tools, including Isaac Gym, Isaac Sim, Aerial Gym. Experience with ROS, and especially real-life aerial robots. Experience with open-source tools for deep learning, computer vision
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following: Prior work with probabilistic deep learning, Bayesian inference, and uncertainty quantification in computer vision. Experience with simulation tools, including Isaac Gym, Isaac Sim, Aerial Gym
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theory around the pace-of-life of marine fish and simulate fast and slow life history strategies within fish populations and fish community food webs. This research aims to examine how these strategies
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the field of electrical engineering or physics. As an ideal candidate, you should also have one or more competences listed below: Experience in simulation, design, and layout of high-frequency integrated
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. This position is funded under a European Research Council (ERC) advanced grant LUMIN (Illuminating charge transport in feldspar to measure rates of Earth surface processes). We are looking for a self-driven and
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with a background in either engineering, mathematics, computer science, computer engineering, physics, sustainable energy, electro-chemistry, and related disciplines, including hands-on experiences
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. Developing state-of-the-art simulation methods for hybrid light-matter systems. Responsibilities and qualifications As a PhD student at DTU, you will Design and develop advanced atomistic simulation
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machine learning to analyse decision-making using diverse data sources, including physiological process data from immersive virtual reality experiments? Do you want to apply cutting-edge modelling and data
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of BSc and MSc. Qualifications MSc graduates with a background in either engineering, mathematics, computer science, computer engineering, physics, sustainable energy, electro-chemistry, and related