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will be tested and verified with applications from geodynamics. For more information consider the job description here . Tasks Tasks in the project include the efficient implementation of new models
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management. Our group combines empirical work (with experiments in the field and in the lab) and modelling techniques. The focus of this postdoctoral position is the generation of empirical datasets
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communication system are modeled using information theory. We wish to investigate how interleaving can reduce the overhead and computational load due to coding coefficients required in classical linear random
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focus on deep networks for solving inverse problems, learning robust models from few and noisy samples, and DNA data storage. The position is in the area of machine learning, with a focus on deep learning
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observations. Generating 3D Models From Visual Data: Imagine creating 3D photos, holograms, or your own custom video game content from a quick video observation. We develop generative 3D models from 2D or 3D
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(with experiments in the field and in the lab) and modelling techniques. The focus of this postdoctoral position is the generation of empirical datasets for livestock systems in East Africa, and in
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, building model checkers (also verified by automated theorem proving) etc. - AUTOMATA TUTOR (available at [1], described in publication [2]) is a tool to teach undergraduate students the basics of theoretical
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observations. Generating 3D Models From Visual Data: Imagine creating 3D photos, holograms, or your own custom video game content from a quick video observation. We develop generative 3D models from 2D or 3D
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located on the new Heilbronn campus (not in Garching / Munich!) Your tasks Graphs are a fundamental data structure and are commonly used to model relationships between data points such as links between web
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of immune cells and in functional assays determining T cell functions - Experience with in vivo experiments in preclinical model systems of viral infection - Excellent writing and communication skills