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Technische Universität Dresden - Center for Interdisciplinary Digital Sciences (CIDS), Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI Dresden)

As part of the German government's artificial intelligence (AI) strategy, the successful Saxon competence center ScaDS.AI Dresden/Leipzig (Center for Scalable Data Analytics and Artificial Intelligence) is being expanded into a leading German AI competence center for Big Data and Artificial Intelligence (AI). For TUD Dresden University of Technology diversity is an essential feature and a quality criterion of an excellent university. Accordingly, we welcome all applicants who would like to commit themselves, their achievements and productivity to the success of the whole institution.

5 Student Assistants (m/f/x) (max. 8 hrs./week)


At the Center for Interdisciplinary Digital Sciences (CIDS), the Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI Dresden) is seeking to employ five positions as

Student Assistant (m/f/x) (max. 8 hrs./week)

starting as soon as possible for a period of 6 months (shortened period due to lecture period, can be extended). The period of employment is governed by the Fixed Term Research Contracts Act (Wissenschaftszeitvertragsgesetz – WissZeitVG) as well as the Higher Education Act in the Free State of Saxony (Sächsisches Hochschulgesetz – SächsHSG) in conjunction with the TdL guidelines (collective bargaining association for the German federal states) for Student Assistants and Research Assistants dated February 28, 2024.

Working field:

Tutor, esp. supporting students, prepare and teach programming lab sessions (“Übungen”), assistance in the preparation of lecture sessions and exam design, including grading. We are looking for students to support us as tutors in the Master lecture "Behind the Secrets of Large Language Models" (WS 2024/25) by Prof. Färber and Prof. Razniewski. The course provides a deep and practical approach into the trending topic of large language models (LLMs), such as ChatGPT. In the lab sessions, students will use the university’s high performance computing (HPC) clusters to train, deploy, prompt, and evaluate recent open-source LLMs.


  • student enrolled at a college/university
  • solid Python programming skills
  • interest in the technical aspects of LLMs (preferable)
  • experience with Deep Learning frameworks (e.g., Pytorch) (preferable)
  • experience in working with the university’s HPC cluster (preferable)
  • theoretical understanding of concepts around LLMs (i.e., Natural Language Processing and Machine Learning) (preferable)
  • experience with training and deployment of LLMs, including Machine Learning models in general (preferable)
  • pedagogic experience, e.g., via previous lab teaching experience (preferable)

How to apply:

TUD strives to employ more women in academia and research. We therefore expressly encourage women to apply. The University is a certified family-friendly university and offers a Dual Career Service. We welcome applications from candidates with disabilities. If multiple candidates prove to be equally qualified, those with disabilities or with equivalent status pursuant to the German Social Code IX (SGB IX) will receive priority for employment.
Please submit your detailed application with the usual Please submit your detailed application including the usual documents (Cover letter, CV, copies of your references and certificates), quoting the job number „ScaDS.AI SecretLLM”, by August 8, 2024 (stamped arrival date of the university central mail service or the time stamp on the email server of TUD applies) to TU Dresden, ScaDS.AI, Herrn Prof. Dr. Michael Färber, Helmholtzstr. 10, 01069 Dresden, Germany or via the TUD SecureMail Portal by sending it as a single pdf file to Please submit copies only, as your application will not be returned to you. Expenses incurred in attending interviews cannot be reimbursed.

Reference to data protection: Your data protection rights, the purpose for which your data will be processed, as well as further information about data protection is available to you on the website: