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learning and advanced statistical modeling * Proficient programming skills in Python and/or R, experience with machine learning and omics analysis libraries (e.g., scikit-learn, TensorFlow/PyTorch
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personal (marriage or civil partnership) or familial (parents, siblings, children) relationship cannot be selected as hosts. Programme information (PDF, 151 KB) Information for academic hosts Information
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available in the further tabs (e.g. “Application requirements”). Programme Description The programme is intended for highly qualified scientists and scholars of all disciplines from selected developing
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from certain countries (see list of countries ). In the event of documented funding issues the Humboldt Foundation is also willing to explore individual solutions and potentially agree exceptions also
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atmosphere in a motivated and friendly team, the opportunity for regular further training and a targeted induction programme Very good work-life balance Max Planck family office, support through an external
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atmosphere in a motivated and friendly team, the opportunity for regular further training and a targeted induction programme Very good work-life balance Max Planck family office, support through an external
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host, who must be working at a university or selected national research institution in Japan. For a corresponding list please see the programme information. Individuals with whom you are in a close
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launched the CAPES-Humboldt Research Fellowship Programme. As a fellow, you will benefit from individual support from the Humboldt Foundation and our diverse sponsorship portfolio. The Alexander von Humboldt
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for applying for a certain fellowship: Appendix; Complete curriculum vitae; List of publications. Important notice for all applicants: Within the DLR-DAAD programme, you can apply only for a DLR institute, not
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available in the further tabs (e.g. “Application requirements”). Objective This scholarship programme allows scientists to carry out research with German colleagues at universities, universities of applied