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Research Associates (Doctoral Candidates) (f/m/d) within the Cluster of Excellence “The Ocean Floor"
ecosystems on the ocean floor react to environmental changes and (iv) develop scenarios for a “warmer world” from climate archives on the ocean floor with the help of climate models. Further information about
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the development of computational methods for genetics, high-throughput omics data and causal discovery. Our interdisciplinary and international team is jointly located at DKFZ and EMBL Heidelberg, and
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following position Postdoctoral researcher (m/f/d) in Environmental Data Science and Machine Learning for the project BoTiKI Location: Görlitz Employment scope: full-time (40 weekly working hours) / part
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relevant experience in management and administration in a similar position; knowledge of the structures of large research groups and university administration Experience in drafting manuscripts and research
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the lab to real-life applications, improving lives. B-cell responses are essential for humoral immunity against pathogens because they lead to the generation of antibody-secreting cells that produce large
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-Firmenticket that is partially subsidized. This is a fixed-term position limited to a period of 3 years. Remuneration is paid according to TVöD Bund, salary group 14. Application and information: We value
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enable the model to infer health-related information directly from NMR spectra of human blood. To this end, the model will be pre-trained using self-supervised learning on large-scale, partly synthetic
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Performing atom probe tomography Application of deep learning algorithms for the correlation of the obtained experimental data and their analysis The majority of the work will be undertaken in Hamburg Your
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. Furthermore, we develop advanced scattering methods and machine learning tools for data analysis. For more information, see www.soft-matter.uni-tuebingen.de Qualification and skills Candidates should have good
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the project »MoGeSa« and develop a detailed Modelica-based simulation model of a floating wind platform for a 15 MW offshore wind turbine. As part of this, you will perform a large number of simulations using