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beam (FIB) imaging - can be combined with AI to reconstruct nanoscale chip structures and infer functional behaviour from physical layouts. The project addresses the challenge of extracting reliable
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structural systems and ULS / SLS design concepts Experience in structural dynamics and/or vibration analysis is an added asset Familiarity with finite element modelling (e.g. ABAQUS) and probabilistic methods
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activity in vitro; basic knowledge of bioinformatics, molecular modelling and docking and/or structural analysis of protein–ligand complexes, as well as the ability to use in silico results to guide
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on developing probabilistic latent-variable methods for large and structured biological data, with applications in genomics, spatial transcriptomics, and fluorescence imaging. High-dimensional and structured
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to the development of a multi-component framework for reliable and computationally efficient fatigue diagnosis and prognosis of steel structures. Building on the group's established expertise in virtual sensing and
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, materials science, polymer engineering, or a comparable field of study In-depth knowledge in the areas of polymer materials, polymer characterization, and data analysis Excellent computer skills and
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on developing probabilistic latent-variable methods for large and structured biological data, with applications in genomics, spatial transcriptomics, and fluorescence imaging. High-dimensional and structured
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, and how strain rate influences material behaviour. The resulting experimental data will be used to validate numerical models and contribute to certification by analysis of future composite structures
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and statistical methods as part of a close collaboration between Uppsala University, Westinghouse, and Vattenfall? Would you like to contribute to the development of fast, robust and reliable
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(between one and two weeks for each mission). A knowledge of various data processing techniques is essential, as is the ability to create reliable databases. Knowledge of the operation of an electrical grid