Offer 172 out of 325 from 17/11/23, 08:44


Tech­ni­sche Uni­ver­sität Ber­lin - Faculty IV - Institute of Software Engineering and Theoretical Computer Science / FG Machine Learning (ML)

Technische Universität Berlin offers an open position:

2 positions - Research Assistant - salary grade 13 TV-L Berliner Hochschulen

under the reserve that funds are granted; part-time employment may be possible

The Konrad Zuse School of Excellence in Learning and Intelligent Systems (ELIZA) is a graduate school in the field of artificial intelligence (Al) funded by the German Academic Exchange Service (DAAD). ELIZA's research and training activities focus on four main topics: the basics of machine learning (ML)- including ML-driven fields like computer vision, NLP, or robot learning -, machine learning systems, applications in autonomous systems, as well as trans-disciplinary applications for machine learning in other scientific fields, from life sciences to physics.

The graduate school offers the funded individuals a combination of excellent, research-based education at the Master's and doctoral level, supervision provided by internationally renowned mentors from both academia and industry, and networking opportunities across different sites.
Coordinated by TU Darmstadt, ELIZA brings together research institutes from seven German citles. They work together under the umbrella of the European Laboratory for Learning and Intelligent Systems (ELLIS), Europe's leading academic network for machine learning-focused Al.

The two positions are part of the ELIZA Graduate School and will be filled at TU Berlin in the Machine Learning research group headed by Prof. Müller. The positions will be co-supervised by Prof. Noé (FU Berlin).

Working field:

The PhD projects will focus on foundational research and current challenges in Al, ML and intelligent data analysis, Including the development of novel theories, algorithms, and technologies, as well as prototypical systems and tools. Possible topics include Bayesian inference, deep learning, reinforcement learning, and secure and explainable ML. Participation in the ELIZA curriculum, including cross-site courses and KI-Campus, and a 6-12 months research stay at another ELIZA site are mandatory.
The opportunity to prepare a PhD thesis is given.


  • Successfully completed academic university degree (Master, Diploma, or the equivalent) in computer science (eg., theoretical, methodological-practical, or technical computer science) of closely related fields of study with a focus on ELIZA's four research core areas,
  • Strong programming skills (e.g., C/C++, Java, Python, Scala),
  • Knowledge of machine learning theorles and methods (e.g., core methods, deep neural networks), practical experience in developing and applying ML algorithms, experlance with linear algebra / neural network frameworks (e.g., NumPy, PyTorch, TensorRlow, JAX),
  • Good knowledge of German and/or English required; willingness to acquire the respective missing language skills

We are looking for higbly mativated, curious, enthusiastic, and cesults orlented researchers with excellent academic records and strong research interest in the area of Ml driven Al

How to apply:

Please send your application, quoting the job reference number and including the usual documents (in particular: letter of motivation, latest CV, copies of your Bachelor's and Master's certificates, official copies of your academic transcripts, list of publications, and names and contact details of at least 2 referees whose letters should be available by the deadline of this call), preferably in English, by e-mail as one file in PDF format to Prof. Dr. Klaus-Robert Müller at

By submitting your application via email you consent to having your data electronically processed and saved. Please note that we do not provide a guarantee for the protection of your personal data when submitted as unprotected file. Please find our data protection notice acc. DSGVO (General Data Protection Regulation) at the Technische Universität staff department homepage: or quick access 214041.

To ensure equal opportunities between women and men, applications by women with the required qualifications are explicitly desired. Qualified individuals with disabilities will be favored. The Technische Universität Berlin values the diversity of its members and is committed to the goals of equal opportunities.

Technische Universität Berlin - Die Präsidentin - Fakultät IV, Institut für Softwaretechnik und Theoretische Informatik, FG Maschinelles Lernen, Prof. Dr. Klaus-Robert Müller, Sekr. MAR 4-1, Marchstr. 23, 10587 Berlin