Sprache:

Facts

Number of employees
rund 7000
Category
Research assistant
Location
Germany, Berlin, Charlottenburg
Area of responsibility
Academia and research, Research (academic)
Start date (earliest)
01.05.2026
Duration
limited until 31.12.2027
Full/Part-time
full-time; part-time employment may be possible
Remuneration
Salary grade 13 TV-L Berliner Hochschulen
Homepage
https://web.ml.tu-berlin.de/

Requirements

Qualification
Master, Diplom or equivalent
Field of study
Computer science

Contact

Reference number
IV-145/26
Contact person
Prof. Dr. Klaus-Robert Müller

Apply

Application deadline
24.04.2026
Reference number
IV-145/26
By email
eliza.applications@ml.tu-berlin.de

Research Assistant

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

Technische Universität Berlin

About us

The Konrad Zuse School of Excellence in Learning and Intelligent Systems (ELIZA) is a graduate school in the field of artificial intelligence (AI) 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 students 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 cities. 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 AI.

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).

Your responsibility

The projects will focus on foundational research and current challenges in AI, 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.

Your profile

  • Successfully completed academic university degree (Master, Diplom, or equivalent) in computer science (e.g., theoretical, methodological-practical, or technical computer science) or 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 theories and methods (e.g., core methods, deep neural networks), practical experience in developing and applying ML algorithms, experience with linear algebra / neural network frameworks (e.g., NumPy, PyTorch, TensorFlow, JAX)
  • Excellent communication skills in English
  • good command of German required; willingness to learn German is expected.

We are looking for highly motivated, curious, enthusiastic, and results-oriented researchers with excellent academic records and strong research interest in the area of ML-driven AI.

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 at least two recommendation letters), preferably in English, by e-mail as one file in PDF format to Prof. Dr. Klaus-Robert Müller at eliza.applications@ml.tu-berlin.de.

By submitting your application via email you consent to having your data electronically processed and saved. Please note that we do not provide a guaranty 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 TU staff department homepage: https://www.abt2-t.tu-berlin.de/menue/themen_a_z/datenschutzerklaerung/.

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 TU Berlin values the diversity of its members and is committed to the goals of equal opportunities. Applications from people of all nationalities and with a migration background are very welcome.

Download PDF