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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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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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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
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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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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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closely linked to the working group of Prof. Ulf Karsten at the University of Rostock and the overarching program “STB – Shallow Water Processes and Transitions to the Baltic Scale” (STB – Processes in
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at: https://www.ipb-halle.de/institut/ Data protection: Please note the data protection information for applicants (m/f/d) in accordance with Art. 13 and 14 GDPR on data processing in the application process
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of traits such as visual anther extrusion, heading date, plant height, and grain yield. You process genotypic data, ensure its alignment with phenotypic data, and conduct association analyses to identify
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Processes and Transitions to the Baltic Scale” of IOW (https://www.io-warnemuende.de/stb-shallow-water-processes.html ), in which physical, chemical and biological oceanographers collaborate to achieve a
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, or in a related discipline Profound data processing and image analysis skills Good knowledge in programming, ideally in Python Ability to work self-reliant and to collaborate in a team of scientists