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, with particular emphasis on exact and nonlinear general relativity, geometric and mathematical analysis of the Einstein equations, analytical and numerical approaches to strong-field dynamics
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and its application to powder diffractometry, X-ray phase analysis, and X-ray structure determination, with an extent of teaching as required by the universities' collective bargaining agreement
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initiative of the Exploratory Modeling of human-natural systems (EM) research group of the Advancing Systems Analysis (ASA) program and the Integrated Assessment and Climate Change (IACC) research group
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data processing chain - from image capture, image processing/computer vision to image content analysis - using both traditional and modern machine learning and AI methods. Your qualifications as an
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where it can be targeted. What you will do Build robust, reproducible scRNA-seq analysis workflows and benchmark methods (simulation + real datasets) Develop rare-event–sensitive CIN/aneuploidy metrics
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and empirical analysis. Your future tasks: The employment aims to deepen and extend the professional and scientific education targeting a PhD. Your areas of work include a scientific research part and a
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from chem- and bioinformatics to computer vision and social network analysis. Machine learning with graphs aims at exploiting the potential of the growing amount of structured data in all these areas
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complexes. Experience in the field of NMR-spectroscopy, analytical HPLC(-MS) as well as preparative HPLC is required. Basic experience in research methods and academic writing. Attention to detail and ability
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data processing chain - from image capture, image processing/computer vision to image content analysis - using both traditional and modern machine learning and AI methods. Your qualifications as an
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controlled systems. The end goal is a mechanistic and clinically relevant map of how CIN shapes cancer behavior and where it can be targeted. What you will do Build robust, reproducible scRNA-seq analysis