Postdoctoral Researcher in Machine Learning & Pediatric Health (80-100%)

• Lead and contribute to ML/AI research projects and publications together with PhD candidates and other postdocs.
• Participate in collaborative projects with clinical and technical partners.
• Support PhD candidates, 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.

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., * 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.

• 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.

The Analytics & Informatics for Child Health (AICH) group embdedded 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.