This pioneering program is ideal for individuals passionate about advancing AI technologies with a focus on safety, security, privacy, and responsibility.

Program Overview

The relAI program addresses a critical gap in AI development by concentrating on the mathematical and algorithmic foundations of reliable AI and its applications in three key areas:

1. Medicine & Healthcare
2. Robotics & Interacting Systems
3. Algorithmic Decision-Making

Participants will benefit from a dynamic research environment in Munich's AI ecosystem, which integrates expertise from Technical University of Munich (TUM) and Ludwig Maximilians University of Munich (LMU). The program also provides opportunities to collaborate with leading global AI centers and industry partners.

What We Offer

• Full Salary: Funded positions with social benefits according to TV-L E13 of the German public sector.
• Travel Grants: Support for attending conferences, research stays, or home travel.
• Comprehensive Training: Cross-disciplinary education, professional development courses, and exposure to industrial applications.
• Guidance: Each PhD student is hosted by a relAI Fellow who provides mentorship and helps define the research project. Students enroll at either TUM or LMU, depending on the Fellow's affiliation.

Eligibility Requirements

Applicants must demonstrate:

• Academic Excellence: A master’s degree (or equivalent) in computer science, mathematics, engineering, natural sciences, or other AI-related disciplines. Students in the final stages of their master’s degree may apply, provided they complete their degree before starting the PhD.
• Interest in Reliable AI: A genuine desire to work on aspects like safety, security, privacy, and responsibility within relAI's focus areas.
• Proficiency in English: Certified English proficiency is required.

How to Apply?

To apply, visit the relAI website for detailed instructions and access to the application portal. The application deadline is January 13, 2025, at 23:59 AoE.

Applicants must submit:

• Academic transcripts or a bona fide statement for ongoing master’s studies.
• Documentation of examination marks (if the degree is incomplete)