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Field
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
modeling of large-scale dynamics in networks. This role involves creating large scale models of dynamic phenomena in electrical power networks and quantifying the risk of rare events to mitigate
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accumulations on our planet. They also break seafloor telecommunication cable networks that form the backbone of global data transfer, and there is emerging understand that they bury globally significant amounts
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, Biophysics/Soft Condensed Matter Theory , Condensed Matter Theory , evolution , Fluid Physics , Material Science , Mechanical Engineering , Network , Nonlinear and Complex Systems , Nonlinear Integral Systems
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researchers to advance Systems Science and Engineering by modeling human behavior in complex dynamic networks addressing global challenges. Emphasizing Cyber-Human-Physical Systems, it tackles issues like
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research and support clinical professionals in providing better patient and population-oriented care in an increasingly complex health care delivery system. Through our research, education (our Population
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Join a young team with a strong national and international network in the field of the rapidly expanding area of metal additive manufacturing at Chalmers University of Technology ! This postdoc
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, and engage with a vibrant network of national and international collaborators. The recruited candidate will work in the AIMLeNS lab lead by Assoc. Prof. Dr. Simon Olsson at Chalmers University
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? With data-driven methods, new opportunities arise to understand ecosystems as complex, dynamic networks. This project aims to analyse the world’s most extensive eDNA database, consisting of weekly
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of the complex networks that the project uncovers. They will be expected to carry out high-level research related to the aims of the research project, submitting publications regularly to refereed journals and
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models to assess the environmental impacts of bio-based products and systems using software tools such as OpenLCA. Analyze complex datasets to identify key areas for improvement in environmental