In the Department of Computer Science at TU Darmstadt, the newly established Research Group “Multimodal Reliable Artificial Intelligence” of Prof. Dr. Marcus Rohrbach invites applications as soon as possible as

Research Assistant (all genders) in Reliable AI

for a period of 3 years. An extension is possible in principle.

The Research Group “Multimodal Reliable Artificial Intelligence” deals with foundational advances at the interface of different modalities, in particular images, videos, and language. Current research focuses on multimodal learning and reliable and secure artificial intelligence and machine learning.

The positions are filled by Prof. Marcus Rohrbach as part of the Alexander von Humboldt Professorship for Artificial Intelligence. The Alexander von Humboldt Professorship is the most highly endowed German science award and is awarded exclusively to top researchers who are world leaders. It enables long-term, forward-looking research to be carried out at universities and universities. Research institutions in this country and makes a lasting contribution to the international competitiveness of Germany as a research location.

The positions focus on the following topics, among others:

  • Self-Awareness of Deep Multimodal Models
  • Selective Prediction
  • Visual Question Answering

The tasks also include scientific services in research and teaching. The opportunity for completing a doctorate (equivalent to a “Ph.D.”) is given – including intensive doctoral supervision.

We offer:

  • Excellent conditions at the Technical University of Darmstadt. TU Darmstadt is regularly ranked as one of the best German computer science faculties, has an outstanding interdisciplinary research profile in artificial intelligence that is unique in Germany and has a powerful AI computing infrastructure.
  • A lively research environment with close interaction with a broad spectrum of renowned and internationally recognized AI scientists (hessian.AI)
  • International conference trips, excellent facilities and extensive training opportunities

Prerequisites:

  • Very good university degree in computer science or a comparable subject.
  • Knowledge in the field of artificial intelligence / machine learning.
  • Very good written and oral English skills.
  • You are highly motivated to publish your results and present them at international project meetings and conferences. If you have previously published it’s a plus.
  • You have excellent communication skills and enjoy working in interdisciplinary and international teams.
  • Very good programming experience, practical experience with pyTorch or comparable deep learning frameworks is advantageous.
  • Ability to work both independently and in a team in a dynamic and interdisciplinary research environment, as well as a high level of motivation and initiative.

The Technical University of Darmstadt stands for excellent and relevant science. Global transformations – from the energy transition to Industry 4.0 to artificial intelligence – challenge us. We play a decisive role in shaping these far-reaching processes of change through outstanding findings and forward-looking courses of study.

Opportunity for further qualification (doctoral dissertation) is given. The fulfillment of the duties likewise enables the scientific qualifications of the candidate.

The Technische Universität Darmstadt intends to increase the number of female employees and encourages female candidates to apply. In case of equal qualifications applicants with a degree of disability of at least 50 or equal will be given preference. Wages and salaries are according to the collective agreements on salary scales, which apply to the Technische Universität Darmstadt (TV-TU Darmstadt). Part-time employment is generally possible.

Applications with cover letter, curriculum vitae and an overview of grades (Bachelor's and Master's) should be sent electronically in a PDF stating the identification number with the subject "Application as a research assistant 532" to: marcus[dot]rohrbach[at]tu[minus]darmstadt[dot]de

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Code No. 532

Published on

September 13, 2023

Application deadline

September 27, 2023