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approximately 30 places. The department strives for an approach that encourages and promotes the use of theories and models drawn not only from traditional social sciences, but also from, for example
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their ability to: independently pursue his or her work collaborate with others, have a professional approach and analyze and work with complex issues. Experience in machine learning, algorithmic theory, or code
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of ecological processes involving animals and plants across a range of spatial and temporal scales understanding of raster data processing including the theory and implementation of relevant algorithms
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sustainability demands of future AI-driven applications. Together, these positions provide unique opportunities to advance both theory and applied technologies in 6G, while contributing to standardization
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inherent complexities. Your role: The doctoral student will conduct research at the intersection of optimization, game theory, and automatic control for complex systems. Their work will encompass both
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content of these processes, studied as a coherent whole. See: https://www.gu.se/en/research/didactic-classroom-studies Phenomenography, Variation Theory, and Learning Study explores questions about how to
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local structure and composition to catalytic behavior. By bridging atomistic theory and machine learning, the work will help explain activity trends and guide the rational design of alloy catalysts
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-dimensional statistics, discrete random structures, insurance mathematics, stochastic control theory and statistical machine learning. Subject: Mathematical Statistics Subject description: Mathematical
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expected to address technical challenges associated with developing software systems, i.e., research on techniques, tools, and theories related to development, maintenance, reliability, performance, and
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expected to address technical challenges associated with developing software systems, i.e., research on techniques, tools, and theories related to development, maintenance, reliability, performance, and