Practical trainings, student assistants and theses

Automated workflows for reproducible benchmarks (Id 328)

Student Assistant / Research Assistant

To establish reproducible benchmarks and data science workflows, we need support from curious collaborators with experience in software development using Python. We would like to extend the open-source Snakemake workflow engine with support for spack/pip environments. Following this task, benchmarks for inference measurement of machine learning systems on local HPC systems will be performed using the above extensions.

Department: Computational Science

Contact: Dr. rer. nat. Steinbach, Peter


  • Programming with Python
  • Code organisation of a Python project (installation, code formatting, tests, integration)
  • Contribution to open source projects on Github


  • Supervision by a team member of the Helmholtz AI Consultants
  • Remote-only work
  • Access to HPC cluster if necessary
  • follow-up projects with machine learning focus possible

Online application

Please apply online: english / german