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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | 16 days ago
of English (Knowledge of German language not required) Additional experience in optics, machine learning, big data, in-strument design, image analysis, or electronics is a plus. Key responsibilities Design
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us to explore the relation between the degree and type of processing, and the foods that result from their use. The results will be used for data machine learning, in collaboration with other partners
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capabilities. Experimental design, laboratory execution, data analysis, and statistical quality control. Required Education PhD Degree in Biochemistry, Molecular Biology, Molecular Genetics, or closely related
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, including three faculty professors, two researchers, several postdoctoral fellows, Ph.D. candidates, data engineers, full and part-time research assistants, administrative support, and several affiliated
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personal interest in pursuing a Postdoc position on the announced topic and at UNIS. Full academic CV. Transcripts and diplomas showing the completion of a PhD degree. Contact information for two references
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interdisciplinary applied research projects. From technological innovation to the transfer of research to industry, Vanguard has also the mission of developing an ecosystem of related start-ups. For more information
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-of-the-art sparse algorithm in matrices, tensor and networks for large-scale numerical, scientific and AI models and disseminating findings through publications and presentations in top-tier peer-reviewed
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). This consortium pulls together expertise from all over the University, including in diagnostics, data science, drug and vaccine design, preclinical testing and clinical testing and brings it to bear on tuberculosis
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that connect animal health, data analysis, and human behavior. Design and carry out field studies, collecting and analyzing large data sets. Use and evaluate AI tools to support research and training. Create
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data storage capacity to accelerate research in intensive computing and large-scale data analytics, commonly referred to as Big Data. This characteristic distinguishes the HPC center at the university