Offer 94 out of 323 from 05/07/24, 08:59


Technische Universität Berlin - Faculty IV - The Berlin Institute for the Foundations of Learning and Data (BIFOLD) / Quality and Usability Lab

Technische Universität Berlin offers an open position:

Research assistant - salary grade E 13 TV-L Berliner Hochschulen - for qualification

part-time employment may be possible

The Berlin Institute for the Foundations of Learning and Data (BIFOLD) at TU Berlin (Prof. Klaus Robert Müller / Prof. Volker Markl) is looking for a research assistant in the field of machine learning and computational linguistics for an agility subproject. The project will be carried out in close cooperation with the Deutsches Herzzentrum der Charité (DHZC) in the "Clinical Data Science" working group led by Prof. Alexander Meyer, and the German Research Center for Artificial Intelligence in the "Speech and Language Technology" department led by Prof. Sebastian Möller.

Prof. Meyer's working group focuses on medical data science, big data analytics, applied machine learning, medical informatics, and cardiovascular medicine. Prof. Möller's department
focuses on applied information extraction, text corpora creation, and explainability among other topics.

Working field:

The goals of the project "Illuminate Cardio" are a) to identify and procure clinical guidelines and patient data from DHC resources, b) to compare and implement approaches to be used in text quality and explanation evaluation suites, c) to develop methods that represent medical information in both accurate and understandable ways, d) to set up and deploy digital health interfaces (DHs) in the DHZC, and e) to conduct long-term studies with both patients and medical professionals interacting with DHIs.

In this project, we expect independent and responsible research in the described areas but also the comparative evaluation of approaches.


  • Successfully completed academic university studies (Master, Diplom or equivalent) in computer science or computational linguistics
  • Experience in natural language processing and machine leaming
  • Experience in conducting user studies (designing annotation guidelines, instructing annotators, consolidating and visualizing results)
  • Very good programming skills in Python, especially in PyTorch/TensorFlow libraries
  • Language skills: The ability to teach in German and/or in English is required; willingness to acquire the respective missing language skills.


  • Desire to work in an agile and lively international and inerdisciplinary environment

Previous experience in one or more of the following areas is preferred:

  • Explainability and interpretability
  • Human-computer interaction, e.g. development of interactive user interfaces and visualizations
  • Information extraction, e.g. from clinical texts
  • Creation and curation of text corpora

How to apply:

Please send your written application, quoting the reference number, with the usual application documents to Technische Universität Berlin - Die Präsidentin - Fakultät IV, Institut für Softwaretechnik und Theoretische Informatik, FG Quality and Usability, Prof. Dr. Möller, TEL 18, Ernst-Reuter-Platz 7, 10587 Berlin oder per E-Mail (eine PDF Datei, max. 5 MB) an: In any case, the documents should include a meaningful cover letter, resume and references.

Application documents sent by post will not be returned. Please submit copies only.

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 TU 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 TU Berlin values the diversity of its members and is committed to the goals of equal opportunities.