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experiments in controlled conditions aiming at simulating natural environments; 3) You will participate in arctic campaigns and use the methods developed to shed light on methane cycling in permafrost regions
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in scientific methodologies that have transformed the study of, and interest for bioarchaeological remains, makes the PhD project highly relevant across multiple academic domains. Although the botany
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/ Robust) Combinatorial Optimization, Game Theory, and Network Theory, as well as Artificial Intelligence. Potentially, scenarios could be simulated using agent-based, discrete-event, or other techniques
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, which has multiple test machines with GPUs and AI accelerators. The algorithms used can be bound by the available compute power or memory bandwidth in different parts of the program. This information will
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for data analysis and modeling. Familiarity with analyzing large-scale healthcare datasets and real-world data. Experience in developing and applying simulation models, including system dynamics, agent-based
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the form of, for example, agentic systems or other abstract AI-pipelines, but research has shown that existing frameworks are brittle. If successful, though, such systems can uncover high-value insights from
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-Jan Reichart Dr Martin Ziegler , and Dr Lennart de Nooijer . Multiple others will be involved for specific aspects of the project. Foreseeable international collaborators include Profs. Stijn de
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simulation techniques based on finite element and multibody dynamics formulations. Your tasks involve developing new elements tailored to the multi-physical effects seen in high-performance mechatronics
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drier with global warming. However, particularly in the vulnerable subtropical and mid-latitude regions, the state-of-the-art climate models produce simulations that differ not only in the magnitude, but
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and is affected by various biogeochemical processes. The processes governing ocean alkalinity act over multiple timescales (from instantaneous chemical equilibration to hundred thousand of years) and