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Field
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techniques from optimization and control theory, scientific machine learning, and partial differential equations to create a new approach for data-driven analysis of fluid flows. The successful applicant will
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The role will develop new AI methods for identifying the instantaneous state of a fluid flow from partial sensor information. The research will couple techniques from optimization and control theory
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on topological quantum matters and cavity vacuum controls driving research activities towards defined goals in specified timeline; publish original research articles in high-impact journals Liaising with project
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/GPUs. These devices provide massive spatial parallelism and are well-suited for dataflow programming paradigms. However, optimizing and porting code efficiently to these architectures remains a key
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. The research group is seeking a talented Doctoral Researcher in nonlinear systems and control with strong interest in nonlinear stability theory, modeling & identification, optimal control, certifiably safe
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Research Assistant/Associate in Photonics Integration of Graphene and Related Materials (Fixed Term)
investigate the large area production of graphene, BN, MoS2 and other layered materials, optimize their transfer process in view of their application in energy, electronics and photonics. This will include
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) platforms used in machine learning, big data and artificial intelligence (AI) based applications (CPUs, GPUs, AI accelerators etc.) require high power demands with optimized power distribution networks (PDNs
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master's degree in agricultural or environmental economics, applied mathematics, or a related fieldGood background in bio-economic modelling, CGE modelling, and optimization techniquesExperience with
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, determining optimal ways for groups of buildings to share resources and benefits. You will investigate and quantify trade-offs between individual objectives and collective outcomes, focusing on scalability
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(HPC) platforms used in machine learning, big data and artificial intelligence (AI) based applications (CPUs, GPUs, AI accelerators etc.) require high power demands with optimized power distribution