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contribute to development of research grant applications. Your profile The applicants should hold a PhD in structural dynamics with focus on data-driven methods (e.g., for input/state/parameter estimation) and
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machine learning methods, including symbolic regression and neural networks. You will apply the algorithms to the discovery of new models in different fields, including robotic control, fluid mechanics and
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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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Postdoc position for the NFC project on Full stack security, at the Department of Computer Scienc...
thereafter. Tasks and qualifications Applicants are expected to have a strong background in computer security, formal methods, or systems. The ideal candidate should have working knowledge of one or more of
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(16): E934-43; Nature Genetics, 2012 Jan; 18;44(1):94-100; Nature, 2011 Dec 14;480 (7378):490-5. You will Lead research on gene regulatory mechanisms Employ state-of-the-art methods in epigenetics and
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Postdoc in atmospheric chemistry on investigating the phase behavior of secondary organic aerosol...
methods to directly probe the phase behavior, i.e., the number and types of phases, in individual aerosol particles, and to explore how it affects their ability to form clouds. The project will focus
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patterns, and extreme climate events remains a subject of debate. Using a combination of climate modelling, statistical methods, and machine learning, ArcticPush aims to uncover the conditions under which