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

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SECAI scholarships were created to support outstanding students who intend to study AI or a related field at TU Dresden or Leipzig University. AI is viewed as an interdisciplinary undertaking that requires talents in computer science, engineering, mathematics, social science, law, the natural sciences, and application areas such as medicine.
The scholarships cover living expenses in Germany to allow students to focus on their studies, kick-start their research career, and build their professional network.
The scholarship is mainly awarded based on academic excellence, but also aims to improve internationalisation and diversity in AI-related teaching programmes. Women in STEM subjects are particularly encouraged to apply. Special personal circumstances are taken into account, for example if students are systematically disadvantaged or prosecuted in their home countries, or are refugees of war.

Highly qualified (current or prospective) Master's students who have achieved excellent results in their Bachelor's studies, and who pursue Master's level studies in Artificial Intelligence, broadly conceived.

Master's students pursuing studies in Artificial Intelligence and related subjects

20

Up to 24 months

The grant consists of a monthly allowance as defined in the SECAI scholarship regulations, currently 934 EUR. Any extra income must be declared, and the scholarship may be reduced by the amount of gross income exceeding 520 EUR. Foreign students may be entitled to a monthly family allowance.

Applications should include the following information and documents:

• Motivation letter, including your topical connection to SECAI and AI in your (planned or current) studies at TU Dresden or Leipzig University
• CV
• Bachelor's certificate (if available), transcript of records, other certificates if relevant
• Declaration of other sources of income, including other scholarships
• If you have applied for admission to a Master's programme in parallel: reference number and submission date of your application.

Incomplete applications cannot be taken into consideration.

Applications for scholarships starting in the winter semester of each year must be received by 19 May (first round) and 30 June (second round) of each year. First-round applications are decided earlier to help with planning.

Students can apply if they meet all of the following criteria:

• They currently are or soon will be students of TU Dresden or Leipzig University at Master's level (it is possible to apply for the scholarship in parallel to applying for a Master's programme; 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 programmes:

- MSc Computational Modeling and Simulation (TUD) in the tracks "AI Engineering", "Logical Modeling", and "Computational Life Science"

- MSc Data Science (UL)

- MSc Nanoelectronic Systems (TUD)

- MSc Bioinformatics (Bioinformatik, UL)

- MSc Medical Informatics (Medizininformatik, UL)

• Moreover, students of other programmes may apply if they have specialised towards an AI-related topic by choice of their elective courses or project/thesis topics. Relevant study programmes include:

- MSc or Diplom programmes in Computer Science

- LLM (Master of Laws) studies with a focus on legal aspects of AI

- MA studies at TUD and UL with a focus on human and societal dimensions of AI

- MSc studies in psychology with a focus on socio-technical systems and human-machine interaction

• 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. Students in German Diplom study programmes are considered to be at the Master's level after they have completed the first two years of their study (Grundstudium).