DAAD Konrad Zuse School of Excellence in Reliable Artificial Intelligence (relAI): Scholarship for Master's Students

DAAD, Germany

Updated: 1 day ago
Deadline: The position may have been removed or expired!

Overview

Eine Druckversion dieser Ausschreibung (PDF) steht Ihnen in den weiteren Registerkarten (z.B. „Bewerbungsvoraussetzungen“) zur Verfügung.

A print version of this announcement (PDF) is available in the further tabs (e.g. “Application requirements”).


Programme Description

The research and training programme focusses on the mathematical and algorithmic foundations of reliable AI along with domain knowledge in three core application domains, for which reliable AI methods are most urgently needed: medicine and healthcare, robotics & interacting systems, and algorithmic decision-making. relAI scholarships are intended to support outstanding students who are studying AI related subjects so they are able to focus on their studies. relAI offers a cross-sectional training for successful education in AI including scientific knowledge, professional development courses and industrial exposure, providing a coherent, yet flexible and personalised training. The scholarship is mainly awarded based on academic excellence, but also aims to improve internationalisation and diversity in AI-related teaching programmes.


Target Group

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


Academic Requirements

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


Number of Scholarships

15


Duration

24 months


Scholarship Value

The scholarship consists of a monthly allowance of currently 934 EUR. Any extra income must be declared, and the scholarship may be reduced by the amount of gross income exceeding 520 EUR.


Application Papers
  • CV
  • Copies of relevant diplomas and transcripts
  • Motivation letter, also highlighting previous experience in the field, e.g. in Bachelor's thesis
  • Proof of English language proficiency: level C1 or equivalent (also acceptable: proof that previous university degree was taught mainly in English)

Application Deadline

Open calls are published on the website .


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