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are being made with incomplete information. Synthetic data offers a way out: realistic-but-artificial datasets that preserve the statistical, temporal and physical structure of real energy data without
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safety, ecosystem degradation, and declining water quality. Given the growing challenges faced by these environments, there is an urgent need to improve our understanding of the physical, ecological, and
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with incomplete information. Synthetic data offers a way out: realistic-but-artificial datasets that preserve the statistical, temporal and physical structure of real energy data without identifying real
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experts on dynamical systems and ergodic theory, postdoctoral researchers Josias Reppekus and Misha Hlushchanka, both active in different areas of complex dynamical systems. PhD students and postdoctoral
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measurements and process-based modelling to identify the mechanisms linking vegetation, soil microorganisms and ecosystem carbon cycling. The project spans laboratory, field and ecosystem scales and combines
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with incomplete information. Synthetic data offers a way out: realistic-but-artificial datasets that preserve the statistical, temporal and physical structure of real energy data without identifying real
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candidates, 7 postdoctoral researchers and 1 PDEng, allowing close collaboration across disciplines including plant physiology, crop modelling, greenhouse technology and systems engineering. As a PhD candidate
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About us You will become part of a collaborative project team, consisting of a PhD researcher (you), a postdoctoral researcher, a junior researcher/research assistant, and three senior researchers
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invasion and plant performance. Working in close collaboration with with a postdoctoral researcher and a fellow PhD candidate, you will identify microbial taxa and microbial interactions that are most
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Are you interested in nanotechnology and experimental condensed matter physics and looking for a PhD position? HFML-FELIX invites applications from motivated candidates for a PhD project in cutting