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, ranging from life sciences to engineering. For more information, visit our webpage www.epc.ed.tum.de/en/mfm. Your profile - M.Sc. degree in informatics, physics, chemistry, or engineering (candidates who
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the Forschungszentrum Jülich`s relevant areas of research Access to a renowned international research network due to the unique position of the NIC Research Groups within the German scientific system Immediate access
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Computer Science or related fields • Strong background in machine learning • Strong programming skills in Python and experience with deep learning frameworks (PyTorch or similar) • Proficient in spoken and written
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plants. In addition to in-depth knowledge of botanical systematics, the application of state-of-the-art methods such as high-throughput sequencing is explicitly desired as part of the current and future
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related field experience in the analysis of high-dimensional biological or medical datasets, ideally in the context of omics technologies proficiency in R/Bioconductor for statistical computing and analysis
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increasingly important, but also more complex, due to rising demands on performance, precision, quality, and sustainability. Bayesian optimization (BO) - a special machine learning approach - represents a
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skills, creativity, a high degree of initiative, and team spirit As an internationally oriented institute, we require excellent English and German skills, both written and spoken Our Offer: An exciting and
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research on democracy. Substantive areas of focus might include the functioning of democratic institutions, internal and external threats facing democracies, and processes of democratization and democratic
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along the entire semiconductor value chain and on tailer-made synthetic diamonds. Whether high-frequency circuits for communications technology, voltage converter modules for electromobility, laser
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in the field of laser technology. In close co-operation with partners from industry and research, the Fraunhofer ILT is working, among other things, on the further development of the additive