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At the Technical Faculty of IT and Design, Department of Electronic Systems, one or more PhD stipends/Integrated PhD stipends in representation, compression, learning, and inference for classical
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, compression, learning, and inference for classical and quantum data exchanged through classical and quantum networks. The objective of the PhD study is to explore and address research and design challenges
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(EBSD, EDX, SAXS, TEM) and ex situ/in situ nanoindentation-based techniques (micro-tensile/compression). The insights gained from this investigation will be crucial for optimizing existing Mg-RE alloys
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advanced microstructural characterization (EBSD, EDX, SAXS, TEM) and ex situ/in situ nanoindentation-based techniques (micro-tensile/compression). The insights gained from this investigation will be crucial
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group has a strong international reputation in academia and industry for pioneering column store technology, fast compression methods, vectorized query execution, indexes for interactive data analysis
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the broad area of analytical database management systems. Our research group has a strong international reputation in academia and industry for pioneering column store technology, fast compression methods
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flow regime ranging from steady laminar to unsteady turbulent configurations, there is also potential to extend the analysis to compressible flows and structural analysis. This research is highly
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of the attachments exceeds 30 MB, they must be compressed before upload. Please note that information on applicants may be published even if the applicant has requested not to be included in the official list
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. Tensegrity structures, which rely on a balance of compressive and tensile components, offer unique advantages for space applications, including high strength-to-weight ratios, flexibility in configuration, and
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efficiency. However, their complex behavior under combined loading conditions—compression, bending, shear, and torsion—poses significant challenges for both design and long-term performance monitoring