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Forschungsinstitut für Nutztierbiologie (FBN) | Dummerstorf, Mecklenburg Vorpommern | Germany | 9 days ago
, climate, video) on different pasture sites Knowledge in the areas of experimental design and statistical data analysis Good written and spoken German and English language skills Driving license class B and
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of Electrical Engineering and Computer Science School of Art and Design Course language German and English Financial support No Structured research and supervision Yes Research training / discussion Yes Career
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by cosmopolitanism, mutual appreciation, thriving innovation and active participation. For TUD diversity is an essential feature and a quality criterion of an excellent university. Accordingly, we
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Requirements: excellent university degree (master or comparable) in computer engineering or electrical engineering a strong background in digital design, hardware description languages (e.g. Verilog, VHDL
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Description As a humanistic, sustainable and action-oriented university, Leuphana University Lüneburg stands for innovation in education and science. Methodological diversity, interdisciplinary
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conduct multifactorial incubation experiments with sediment cores to assess the role of temperature, as well as oxygen and nutrient concentrations as drivers of N2 O cycling within upper sediments and at
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profile A completed PhD in psychology, educational measurement, statistics, or a related field Solid knowledge of psychometrics and experience with statistical software (e.g., R) Strong interest in
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control, human-robot collaboration, and smart grids. For this reason, their design and deployment should be accompanied by a formal check of correct behaviour. The Research Training Group on Continuous
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responsibilities: To carry out and complete your own research towards a doctoral degree. Design, run, and analyse equilibrium simulations with a coupled Earth-system model of intermediate complexity to investigate
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generating a high-quality training dataset to support the development of the AI foundation model Contributing to the design and implementation of advanced deep learning architectures (e.g., Transformers, CNNs