Relai Phd Program: Call for Applications - Munich, Deutschland - Technische Universität München

Technische Universität München

Geprüftes Unternehmen

Munich, Deutschland

vor 4 Tagen

Geschrieben von:

Lena Wagner

beBee Recruiter

Beschreibung

The Konrad Zuse School of Excellence in Reliable AI (relAI) aims to train future generations of artificial intelligence (AI) experts, who for the first time combine technical brilliance with awareness of the importance of AI's reliability.**
Applications for the relAI PhD program are now open
***
The current technological revolution is largely driven by spectacular progress in AI.
Yet, although the huge potential is widely recognized, the lack of a reliable AI technology whose fundamental bases are safety, security, privacy and responsibility, is still considered a serious issue of concern, limiting its adoption both by industry and society at large.

The relAI school is embedded in the unique transdisciplinary Munich AI ecosystem, combining the expertise of the two Universities of Excellence Technical University of Munich (TUM) and Ludwig Maximilians University of Munich (LMU) and closely integrates various AI Centers of leading universities worldwide and industry partners.

What the relAI PhD program offers
***
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.

Eligibility
***
Excellent master's degree (or equivalent) in computer science, mathematics, engineering, natural sciences or other data science/machine learning/AI related disciplines.

Applicants should have a genuine interest to work on a topic of reliable AI covering aspects such as safety, security, privacy and responsibility in one relAI's research areas Mathematical & Algorithmic foundations, Algorithmic Decision-Making, Medicine & Healthcare or Robotics & Interacting Systems.

How to apply
***-
If you are still studying for your master's degree you may send a bona fide statement/transcript from the university, stating the examination marks already obtained. In addition, you will have to finish your master's studies before starting the PhD.

The Konrad Zuse School of Excellence in Reliable AI (relAI) aims to train future generations of artificial intelligence (AI) experts, who for the first time combine technical brilliance with awareness of the importance of AI's reliability.

Applications for the relAI PhD program are now open
The current technological revolution is largely driven by spectacular progress in AI.

Yet, although the huge potential is widely recognized, the lack of a reliable AI technology whose fundamental bases are safety, security, privacy and responsibility, is still considered a serious issue of concern, limiting its adoption both by industry and society at large.

The relAI school is embedded in the unique transdisciplinary Munich AI ecosystem, combining the expertise of the two Universities of Excellence Technical University of Munich (TUM) and Ludwig Maximilians University of Munich (LMU) and closely integrates various AI Centers of leading universities worldwide and industry partners.

What the relAI PhD program offers

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.

Eligibility
Excellent master's degree (or equivalent)* in computer science, mathematics, engineering, natural sciences or other data science/machine learning/AI related disciplines.

Applicants should have a genuine interest to work on a topic of reliable AI covering aspects such as safety, security, privacy and responsibility in one relAI's research areas Mathematical & Algorithmic foundations, Algorithmic Decision-Making, Medicine & Healthcare or Robotics & Interacting Systems.

How to apply

If you are still studying for your master's degree you may send a bona fide statement/transcript from the university, stating the examination marks already obtained. In addition, you will have to finish your master's studies before starting the PhD.

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