Research Engineer and Administrator

Department of Biomedical Engineering (DBE), University of Basel

Group:
Analytics & Informatics for Child Health (AICH)
Starting date:
As soon as possible or upon agreement
Duration: 2 years, with possibility of extension

The Analytics & Informatics for Child Health (AICH) group develops AI/ML methods, digital tools, and secure data pipelines to advance pediatric healthcare. We work at the intersection of clinical medicine, machine learning, and data‑intensive research, collaborating closely with hospitals, clinical IT teams, and research partners at the University of Basel.

In this hybrid role you will support research engineering and local IT administration for the AICH group.

• Research Engineering (approx. 60%)
  • Develop and maintain data pipelines and reproducible ML/AI workflows (Python).
  • Support clinical data ingestion, pseudonymization, and secure transfer to cluster environments.
  • Build and manage containerized environments (Docker, Singularity) and orchestrate jobs via SLURM.
  • Support researchers (PhD students / Postdocs) with data preparation, prototyping, and code organization.
  • Contribute to infrastructure for MLOps (logging, experiment tracking, reproducible setups).
  • Collaborate in ML/AI research projects and publications together with PhD students and postdocs.
  • Participate in collaborative projects with clinical and technical partners.
• IT Administration (approx. 40%)
  • Maintain local group IT infrastructure (user accounts, laptop setup, access control, basic troubleshooting).
  • Coordinate with Uni Basel HPC and DBE IT services (network access, storage, permissions, security).
  • Ensure data security and compliance for sensitive health data (in collaboration with clinical IT partners).
  • Manage group website updates and support digital communication tools.
  • Oversee software licensing, hardware procurement, and inventory.

• Master's degree in Computer Science, Software Engineering, Data Engineering, or a related field.
• Strong programming skills in Python; experience with shell scripting.
• Familiarity with HPC or cloud compute environments, or motivation to learn SLURM/HPC workflow management.
• Familiarity with cloud or HPC environments.
• Understanding of data privacy and security, ideally in a clinical or research context.
• Experience with ML/AI workflows (MLFlow, PyTorch, W&B) is a plus.
• Knowledge of CMS systems (Word Press/Drupal) is an advantage.
• A high degree of independence: able to take ownership of tasks, drive projects forward, and proactively identify solutions.
• Strong problem‑solving mindset; proactive and reliable.
• Clear communication, willingness to support colleagues, and comfort working in interdisciplinary teams.
• Fluent in English (spoken and written). German is an advantage but not required.

• An exciting and meaningful role at the interface of medicine, AI, and digital health.
• A supportive and interdisciplinary research environment combining clinical, technical, and scientific work.
• Access to state‑of‑the‑art computing infrastructure (HPC clusters).
• Opportunities for professional growth (HPC, MLOps, ML engineering, research software engineering).
• Depending on the candidate's background and research interest, the role may include participation in ML/AI publications.
• Flexible working arrangements and a collaborative team culture.
• Employment conditions in accordance with the University of Basel.

Please submit the following as a single PDF:

• CV
• Cover letter
• Contact information for 2–3 references
• (Optional) Links to Git Hub/portfolio or previous technical work

Applications should be sent via the University of Basel application portal.

For further questions, please reach out directly to Prof. Dr. Ece Özkan Elsen (ece.oezkanelsen).