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actively participate in research, teaching & administration, which means: Merging computer science and qualitative and quantitative social science methods, you explore the conceptual data models
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influences water dynamics and greenhouse gas (GHG) fluxes using state-of-the-art geophysical methods (e.g., geoelectrical methods and nuclear magnetic resonance techniques) and biogeochemical measurements
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home of several third-party funded research projects. Through cooperation with numerous academic institutions worldwide, the Department is very well connected with the international scholarly community
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to research and teaching in the field of quantitative social research. The focus is on the innovative application and/or further development of complex methods and new approaches in quantitative empirical
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. Interests could include geological field-based methods and big data applications and machine learning methods. Research focus will be on feedback processes between erosion, sedimentation, tectonics and
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a variety of approaches, such as stochastic processes, kinetic theory, variational analysis, finite element methods, and data-driven techniques. The Vienna School of Mathematics doctoral program
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to bridge the gap between regulatory aspirations and real-world constraints and outcomes, offering innovative approaches to compliance monitoring in an era where traditional methods are increasingly
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pertaining to organizational design decisions relevant to firms operating in (technologically) innovative environments. We are agnostic to methods and pursue formally analytical, simulation-based, ethnographic
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and developmental biology, chromatin, RNA and chromosome biology, and synthetic/computational methods (including AI/ML) that will address complex biological questions from a mechanistic angle. Together
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materials discovery and machine-learning-accelerated materials simulation. You lead and guide the development of novel computational materials discovery and molecular simulation methods. You take a key role