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contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with
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Post doc position in theory of machine learning at Department of Computer Science, Aarhus University
is on understanding and improving the performance of classic learning algorithms, in particular Boosting and Bagging, both in terms of speed and generalization capabilities. The project also allows
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mechanism. Recent developments in protein structure prediction and protein de novo design have opened new possibilities for probing such mechanisms. The project will seek to use existing algorithms to new
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technologies such as artificial intelligence (A), big data, and algorithmic decision-making become increasingly embedded in organizational practices, companies face new ethical, societal, and managerial
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. The position focuses on frequency-domain electromagnetic (FEM) and transient electromagnetic (TEM) methods. The successful candidate will contribute to the development of an inversion framework for the joint
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description Research in this project involves a synergistic combination of intelligent control and aerial robotics for the navigation in uncertain environment. You will be mainly responsible for: development