Postdoctoral Researcher in Machine Learning&Pediatric …, Basel

Postdoctoral Researcher in Machine Learning&Pediatric Health (80-100%) University of Basel ranks among the world’s one hundred best universities and boasts a top-ten place among German-speaking universities.

Department of Biomedical Engineering (DBE), University of Basel

Group:

Analytics&Informatics for Child Health (AICH)

Starting date:

July 2026 or upon agreement

Duration:

2 years, with possibility of extension

About Us

The Analytics&Informatics for Child Health (AICH) group embedded in BRCCH (Basel Research Center for Child Health) 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.

We are looking for a motivated

Postdoctoral Researcher

who combines strong research skills in ML/AI with an interest in applied digital health problems and hands‑on experience with research engineering and data infrastructure.

Research (approx. 80%)

Lead and contribute to ML/AI research projects and publications together with PhD students and other postdocs.

Participate in collaborative projects with clinical and technical partners.

Support PhD students, master students or interns with data preparation, prototyping, and code organization.

Build and manage containerized environments (Docker, Singularity) and orchestrate jobs via SLURM.

Contribute to MLOps infrastructure (experiment tracking, logging, reproducible setups).

IT Administration (approx. 20%)

Maintain local group IT infrastructure.

Coordinate with UniBasel HPC and DBE IT services (network access, storage, permissions, security).

Develop and maintain data pipelines including clinical data ingestion, pseudonymization, and secure transfer to cluster environments, in compliance with data security requirements and in collaboration with clinical IT partners.

Manage group website updates and support digital communication tools.

Oversee software licensing, hardware procurement, and inventory.

Qualifications

PhD in Computer Science, Machine Learning, Biomedical Engineering, or a related field.

Strong publication record in ML/AI or related areas.

Solid programming skills in Python; experience with ML frameworks (PyTorch, TensorFlow) and workflow tools (MLFlow, W&B).

Experience with HPC or cloud compute environments.

Interest in clinical or health data applications; experience with sensitive data handling is a plus.

A high degree of independence and ability to drive projects forward proactively.

Strong communication skills and comfort working in interdisciplinary teams.

Fluent in English (spoken and written). German is an advantage but not required.

Benefits

A research-focused role at the interface of machine learning, clinical medicine, and digital health.

A collaborative and interdisciplinary environment with close ties to clinical partners.

Access to state‑of‑the‑art HPC computing infrastructure.

Opportunities for career development in ML research, research engineering, and academic leadership.

Flexible working arrangements and a supportive team culture.

Employment conditions in accordance with the University of Basel.

Application / Contact

Please submit the following as a single PDF:

CV

Cover letter describing your research interests and relevant experience

Contact information for 2–3 references

(Optional) Links to GitHub/portfolio or previous technical work

Applications should be sent via the University of Basel application portal or directly to:

Prof. Dr. EceÖzkan Elsen

Department of Biomedical Engineering

University of Basel

Email:

#J-18808-Ljbffr