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consisting of PAT and mechanistic / data driven modelling allowing process control. Steps to be taken will be: Developing a process applicable PAT method (single / multisensoric) for AAV / LNP / VLP detection
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to an unprecedented extent. The main topics include the description and modelling of wind turbulence, the analysis of interactions of turbulent atmospheric wind flow and wind energy systems, as well as control of wind
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. The acronym CAUSE stands for Concepts and Algorithms for - and Usage of - Self-Explaining Digitally Controlled Systems. Digitally controlled systems are ubiquitous in our everyday lives, from transportation
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of models in existing simulation software conducting numerical studies, also on HPC systems Further specific tasks can be tailored to the attitude and interests of the PhD students/postdocs. Requirements
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are an advantage: femtosecond laser and diagnostics, high power lasers, ultrahigh vacuum, programming skills (Labview, Python) Ability to work closely within a team: engineers, students, postdocs and scientists, and
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coherent and incoherent seed sources Implement intelligent control over spectral and temporal shapes of broadband nanosecond laser pulses Broadband UV-generation position Implement nonlinear multi-pass cells
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-resilient woody plants (LaserRoots)’, which is funded by the European Regional Development Fund (EFRE). The sub-project of Leibniz Universität Hannover ‘SteBeLa: Control and evaluation of laser-induced
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Engineering, Program Analysis and Formal Methods We constantly seek applications from qualified researchers regardless of their national origin or citizenship. The working language is English. A command of
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Engineering, Program Analysis and Formal Methods We constantly seek applications from qualified researchers regardless of their national origin or citizenship. The working language is English. A command of
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patient-derived, isogenic-corrected patient-derived controls and healthy-derived iPSCs and evaluate pathomechanisms through in-depth molecular, physiologic, and morphologic phenotype analysis. WP2