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project, a machine learning algorithm will be developed for magnetic systems. Specifically, the project aims to solve non-linear magnetic equations (e.g. macroscopic Maxwell equations) using physically
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As Austria's largest research and technology organisation for applied research, we have set ourselves the goal of making substantial contributions to solving the major challenges of our time, climate change and digitisation. To achieve our goals, we rely on our specific research, development and...
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8 May 2024 Job Information Organisation/Company Johannes Kepler University Department the Institute for Machine Learning Research Field Computer science Researcher Profile Recognised Researcher (R2
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8 May 2024 Job Information Organisation/Company Johannes Kepler University Department the Institute for Machine Learning Research Field Technology Researcher Profile Recognised Researcher (R2
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Machine Learning. The successful candidate will work in the group of the START research project "Universal structures in Mathematical Finance", led by Prof. Christa Cuchiero. The focus of the project lies
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for the position of one to two Prae-Docs (3 year appointment, 30 hours) at the intersection of Mathematical Finance, Stochastic Analysis and Machine Learning. The successful candidate will work in the group
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of one to two Prae-Docs (3 year appointment, 30 hours) at the intersection of Mathematical Finance, Stochastic Analysis and Machine Learning. The successful candidate will work in the group of the START
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/ artificial intelligence / machine learning methods with perspectives from technology innovation, government, business, and society that focus on driving climate action. You will be immersed in
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number of possible applications cannot be mapped experimentally, you then use established model-based approaches to train machine learning models that can be used to conveniently examine systems with a
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sensors and cameras and design scalable embedded vision systems and apply machine learning methods (for e.g., deep learning) to conduct high-performance visual quality inspections of products in