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investigate new insights across disciplines, including sociology, political science, computational social science, and data science; You will contribute to the theoretical development of the concept
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electromagnetic signatures, primarily focussed on linking the data from these exciting experiments with our theoretical understanding of gravity and the most extreme regions of the Universe. I am a member of the
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matter • Physical phenomena in reduced dimensions • Soft matter and the physics-biology interface The first theme encompasses both experimental and theoretical studies on the properties of systems
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Research Center Borstel - Leibniz Lung Center | Hamburg Gro Borstel, Hamburg | Germany | 2 months ago
Bioinformatics or in Computer Science, Data Science, Statistics, etc. with focus on molecular biology • Strong quantitative and analytical skills, with a keen interest in microbial genomics and host-pathogen
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of Theoretical Physics (ITFA) and the Institute for High Energy Physics (IHEF) and is one of the large research institutes of the Faculty of Science at the University of Amsterdam. The Van der Waals - Zeeman
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information-theoretic approach that embeds security directly into the physical transmission layer, ensuring resilience against future attack methods, e.g., by quantum computers. We are seeking a highly
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Germany Type of Contract To be defined Job Status Other Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research
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Position Description The theoretical astrophysics and cosmology group at IGFAE invites applications for a 4-year PhD position focused on galaxy formation and evolution, to be supervised by Marta
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the center's partner enterprises. Qualifications Essential Requirements: A Ph.D. (obtained or soon to be obtained) in Automation, Computer Science, Artificial Intelligence, Mechatronics, Mechanical Engineering
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before the deadline. In many applications such as biological sciences, social science, and engineering, we encounter high-dimensional observations. Bayesian approach can provide a flexible modeling