Image result for DAAD Zuse School of Embedded Composite Artificial Intelligence (SECAI) DAAD Zuse School of Embedded Composite Artificial Intelligence (SECAI): Scholarships for Master's students in AI

open8 AufrufeGlobal

DAAD Zuse School of Embedded Composite Artificial Intelligence (SECAI): Scholarships for Master's students in AI

DAAD Zuse School of Embedded Composite Artificial Intelligence (SECAI)

This scholarship supports outstanding Master's students studying AI or a related field at TU Dresden or Leipzig University. It covers living expenses in Germany, with a monthly allowance of 934 EUR, and is awarded based on academic excellence, internationalisation, and diversity.

Wer kann sich bewerben

Highly qualified current or prospective Master's students at TU Dresden or Leipzig University with excellent Bachelor's results (GPA 1.7 or better in German system) and studies closely related to SECAI research areas.

Vorteile und Vergünstigungen

Living expenses coverage
Monthly allowance

Wichtige Kontakte

Herr Philipp Hanisch
Contact
[email protected] +49 351/46343506

Quellen

Links, die von der KI zur Sammlung von Informationen über diesen Zuschuss verwendet wurden.

Finanzierung

€934 – €934

Frist

30. Juni 2026

Öffnet

31. Mai 2026

Webseite des Veranstalters Quelle ansehen

Registrieren Sie sich für automatische Treffer bei Zuschüssen wie diesem.

Kostenlos starten

Eignungskriterien

They currently are or soon will be students of TU Dresden or Leipzig University at Master level (it is possible to apply for the scholarship in parallel to applying for a Master's program; this requires two independent applications).
The content of their studies are closely related to the research areas of SECAI. This includes but is not limited to studies in the following programs: M.Sc. Computer Science (TUD), M.Sc. Computational Modeling and Simulation (TUD) in tracks Applied Artificial Intelligence and Computational Life Science, M.Sc. Data Science (UL), M.Sc. Nanoelectronic Systems (TUD), M.Sc. Bioinformatics (Bioinformatik, UL), M.Sc. Medical Informatics (Medizininformatik, UL).
All applicants must demonstrate an above-average academic track record, typically with a cumulative grade point average of 1.7 or better (after conversion to the German grading system). Exceptions may be made in case of adverse personal circumstances.