Retinal Imaging Data Scientist & Disease Progression Lead

Universität Basel; Basel; On-site; CHF 90,000 - 130,000; Full time

Benefits offered by this job

Public transport access

Subsidized meals

Childcare support

Unisport access

Job summary

The Institute of Molecular and Clinical Ophthalmology Basel (IOB) invites applications for a Research Associate / Bioinformatician to join the Retinal and Macular Degeneration Clinical Research Group in Basel. You will lead quantitative analysis of retinal imaging data and develop models for disease progression using high-dimensional imaging features.

Collaborating with clinicians, you will translate computational findings into trial design and patient selection criteria, contribute to

Qualifications

• MSc or PhD in a quantitative field (e.g., computational biology, bioinformatics).
• Strong Python programming and reproducible data-analysis workflows.
• Experience with complex high-dimensional biomedical/imaging datasets and QC.
• Ability to explain methods clearly to computational and clinical colleagues.
• Evidence of independent quantitative research (thesis/publication/software).

Responsibilities

• Analyze large-scale retinal imaging datasets using deep-learning imaging features.
• Develop and validate statistical and machine-learning models of disease progression.
• Build patient stratification and phenotyping pipelines.
• Collaborate with clinicians to translate findings into trial design and endpoints.
• Contribute to publications and present findings at international conferences.

Skills

Python programming

Data analysis

High-dimensional data

Explain results

Independent research

Education

MSc/PhD in computational biology

Job description

The Institute of Molecular and Clinical Ophthalmology Basel (IOB) invites applications for a Research Associate / Bioinformatician to join the Retinal and Macular Degeneration Clinical Research Group in Basel. You will lead quantitative analysis of retinal imaging data and develop models for disease progression using high-dimensional imaging features.

Collaborating with clinicians, you will translate computational findings into trial design and patient selection criteria, contribute to