We are excited to announce that our second call for applications to the fully funded PhD program of our Konrad Zuse School of Excellence in Reliable AI (relAI) is now open.
Spread the word and submit your application by January 15th, 2024 here.
application
We are excited to announce that applications for the relAI Master program are now open. Interested candidates can apply through our website. Deadline for applications is June 16th, 2023.
The novel, innovative MSc relAI program 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.
Funded applicants will receive a stipend of up to 934 EUR (depending on independent income). We expressly encourage international students to apply. They will be further supported by travel grants for home travel.
We encourage candidates with an excellent bachelor’s degree (or equivalent) in computer science, mathematics, engineering, natural sciences or other data science/machine learning/AI related disciplines and a genuine interest to work on a topic of reliable AI to apply (in parallel to applying for a master program at TUM or LMU).
We are excited to announce that applications for the relAI PhD program are now open. Interested candidates can apply through our website. Deadline for applications is January 9th, 2023.
The novel, innovative PhD relAI program 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.
Funded applicants will be hired for three years, including social benefits (TV-L E13 of the German public sector). They are further supported by travel grants, e.g. for conference attendance or research stays. Doctoral students enrol at TUM or LMU depending on the hosting relAI fellow.
We encourage candidates with an excellent master’s degree (or equivalent) in computer science, mathematics, engineering, natural sciences or other data science/machine learning/AI related disciplines and a genuine interest to work on a topic of reliable AI to apply.