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such as the NEPS. Potential research areas include (but are not limited to): Item response modeling of achievement tests Analysis of process data (e.g., response times) to enhance competence measurements
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. The department of Atmospheric Chemistry (ACD) and Atmospheric Microphysics (AMP) research the chemical and physical properties of aerosol particles and their interactions with clouds. Process-based laboratory
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and under the impact of the food supply chain, including food processing. In this context, the aim of the PhD project is to investigate the influence of drought stress on sulphur-containing plant
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include application of process-based models (e.g., CANDY, DayCent, LDNDC, Daisy) to model within-field N-fluxes (e.g., N2O-losses, NO3-leaching, N-mineralization) support model parametrization, estimate N
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) according to Article 13 and 14 GDPR on data protection processing during the application process: https://www.ipb-halle.de/en/career/data-protection-information-for-applicants/
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/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages
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Association. At the Leibniz Institute on Aging – Fritz Lipmann Institute (FLI), we investigate the fundamental biological processes that drive aging. Our research combines molecular, cellular, and systems-level
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and quantify water mass transformation (WMT) processes in the Skagerrak, connecting the North Sea and the Baltic Sea. The Consortium members study these WMT processes by developing and applying WMT
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organizational levels of the brain – from molecular and cellular processes to complex neuronal networks and behavior. The Department Cellular Neuroscience of Prof. Dr. Stefan Remy in association with the Research