Stellenticket Humboldt-Universität zu Berlin

The group "Big Data Engineering" (DAMS Lab), headed by Prof. Dr.-Ing. Matthias Böhm, conducts teaching and system-oriented research in the area of data management for the end-to-end data science lifecycle from data integration, cleaning, and preparation, over efficient and scalable model training, to model debugging and deployment.

The DAMS Lab research group is looking for a research associate (d/m/w) to join the team with a special focus on system infrastructure for data-centric machine learning pipeline sand their efficient and scalable execution in local and distributed environments. Topics of interest include:

• Language abstractions for data-centric machine learning (ML) pipelines
• Efficient training and inference of Large Language Models (LLMs)
• Compilation techniques for linear algebra programs
• Runtime kernels and parallelization strategies for linear algebra programs
• ML system internals like memory management and I/O
• Support for heterogeneous hardware accelerators
• Teaching tasks

• Successfully completed academic university degree (master's degree, diploma or equivalent) in Computer Science or a related field of study. We are also open to domain-specific backgrounds if there is a willingness to close any gaps in the necessary CS background.
• Strong background in the areas of data management, applied machine learning, distributed systems, and software engineering
• Programming experience in Python and Java (mandatory) as well as C/C++ (advantage)
• The ability to teach in German and/or in English is required; willingness to acquire the respective missing language skills
• Ability to communicate and work in a team, independent working style, high motivation is desiable
• Basic experience in research methods and scientific writing is desirable
• Experience in teaching and didactic competence is an advantage

Please send your application with the reference number and the usual documents (Cover Letter, CV, transcripts, degrees; in one file max. 10 MB) only via email to jobs@dams.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.