70 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" uni jobs at DAAD
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documents by March 26, 2026 (stamped arrival date of the university central mail service or the time stamp on the email server of TUD applies), preferably via the TUD SecureMail Portal https://securemail.tu
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metamaterials. The successful candidate participates actively in the qualification program and general scientific activities of D³. More information can be found at https://tu-dresden.de/ing/forschung
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research with the combined tools of immunology, microbiology, virology, cell biology and molecular biology. For more information, please see https://www.mhh.de/hbrs/zib MD/PhD Molecular Medicine
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Description For our location in Hamburg we are seeking: Doctoral Researcher in Machine Learning and Data Processing in the Field of Seismic Measurements Remuneration Group 13 | Limited: 3 years
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successful candidate will be employed by the MBN Research Center gGmbH in Frankfurt am Main, Germany, and enrolled in the PhD programme at the Goethe University Frankfurt. MBN Research Center ( https
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successful candidate will be employed by the MBN Research Center gGmbH in Frankfurt am Main, Germany, and enrolled in the PhD programme at Goethe University Frankfurt. MBN Research Center ( https
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this with expertise in high-performance computing and artificial intelligence using unique scientific infrastructures. Are you excited about working at the interface of natural and computer sciences? At
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learning new techniques The University of Regensburg aims to increase the proportion of women and therefore explicitly encourages qualified women to apply. The University of Regensburg is particularly
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, biochemical interactions and biological functions of small natural product molecules in and from plants and fungi ( https://www.ipb-halle.de/en/ ). Contact details: We are looking forward to receiving your
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and training provision within CAFE-BIO are available from the network website ( https://cafe-bio.org ) and the official EU page for the network ( https://cordis.europa.eu/project/id/101226762