Experience with high-dimensional genomic data analysis
Proficiency in r and/or python programming
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Roche is seeking a motivated computational scientist to join their Ophthalmology therapeutic area in Basel, Switzerland. The role involves analyzing high-dimensional datasets to identify therapeutic targets and biomarkers, contributing to innovative medicines for ocular diseases within a collaborative and data-driven culture.
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Job Summary
This role involves analyzing complex, high-dimensional datasets to identify novel therapeutic targets and biomarkers for ocular diseases.
The position requires collaboration with interdisciplinary teams including laboratory scientists, clinicians, and computational experts to advance drug discovery efforts.
Candidates will contribute to a culture defined by curiosity, responsibility, and humility while helping Roche transform science into life-changing medicines.
Matching Summary
Match Score: 75
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Roche is seeking a motivated computational scientist to join their Ophthalmology therapeutic area in Basel, Switzerland. The role involves analyzing high-dimensional datasets to identify therapeutic targets and biomarkers, contributing to innovative medicines for ocular diseases within a collaborative and data-driven culture.
**
Skills & Requirements
Must-have
PhD in Bioinformatics or Computational Biology
Experience with high-dimensional genomic data analysis
Proficiency in R and/or Python programming
Knowledge of Linux/Unix and HPC cluster processing
Background in disease biology and drug discovery
Nice-to-have
Specific expertise in ophthalmology disease areas
Experience collaborating with AI/ML colleagues
Track record of working alongside experimental scientists
Strong communication skills for non-specialist audiences
Key Requirements
PhD in Bioinformatics, Biostatistics, or related field
Demonstrated experience in drug discovery or translational research
Evidenced programming skills in R and/or Python
Working knowledge of Linux/Unix environment
Commitment to clean, well-documented code and reproducible research