13 postdoc-in-thermal-network-of-the-physical-building PhD scholarships at Linköping University
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Sklodowska-Curie Doctoral Network FADOS. The successful candidate will join a cohort of 17 doctoral students based at 16 research groups in Europe and the UK. About FADOS FADOS, Fundamentals and Applications
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European Marie Sklodowska-Curie Doctoral Network FADOS. The successful candidate will join a cohort of 17 doctoral students based at 16 research groups in Europe and the UK. About FADOS FADOS, Fundamentals
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8 Oct 2025 Job Information Organisation/Company Linköping University Research Field Physics Researcher Profile First Stage Researcher (R1) Country Sweden Application Deadline 10 Nov 2025 - 12:00
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, undergraduate and postgraduate education in communications engineering, statistical signal processing, network science, and decentralized machine learning. Welcome to read more about us at: https://liu.se/en
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convolutional neural networks by exploring transformers, implicit neural representations (INRs), and hybrid architectures that integrate physical priors such as periodicity, symmetry, and long-range correlations
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Communications in Networked Systems: A Data Significance Perspective” published in IEEE Network, vol. 36, July/August 2022. The project is part of a collaboration between Linköping University and Lund University
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of Communication Systems carries out research, undergraduate and postgraduate education. We conduct research and education in communications engineering, statistical signal processing, network science, and
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fast-paced research environment, a structured and organized approach is highly valued. You will work in a team of researchers from diverse backgrounds, including PhD students and postdocs, and should
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student and help build tomorrow’s craft and design heritage. Craft the future! Your work assignments The aim of this doctoral position is to explore how new design languages and aesthetic expressions can
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well as postgraduate and undergraduate education within areas such as autonomous systems, complex networks, data-driven modeling, learning control, optimization, and sensor fusion. The division has extensive