Sr. Scientist, Computational Biology - Neuroscience & Rare Diseases

Senior Scientist in Computational Biology within Roche's Computational Sciences Centre of Excellence, focused on Neuroscience and Rare Diseases.

The Computational Biology and Medicine department focuses on furthering understanding of disease pathogenesis, patient populations, and target biology by having access to the largest Pharma R&D datasets in the world.

The Opportunity

You will be a key member of an interdisciplinary team dedicated to advancing understanding of neurological diseases. You will identify novel therapeutic targets and biomarkers by analyzing high-dimensional data. You will collaborate closely with leading laboratory scientists and clinicians, contributing directly to a pipeline of innovative medicines for patients with neurodegenerative and neuroinflammation diseases.

Data Analysis & Insight Generation

• Lead the analysis of high-dimensional datasets such as single-cell, spatial, proteomics, metabolomics, and human genetics data to support therapeutic and biomarker development
• Collaborate closely with the AI/ML Foundation Model development teams and apply advanced quantitative methods, supporting drug discovery projects in Neuroscience and Rare Diseases
• Deliver clear and objective data-driven insights to inform portfolio decision-making

Collaboration & Strategy

• Contribute to the data and analytics strategy for Neuroscience and Rare Diseases efforts
• Develop effective working relationships with key stakeholders in the disease therapeutic area, laboratory teams, and computational teams

Requirements

• PhD in Bioinformatics, Biostatistics, Computational Biology, or similar field with 3-5 years relevant work experience preferred
• Demonstrated experience in drug discovery and/or translational research
• Experience in disease biology required; expertise in neurodegenerative diseases or neuro-immune interactions is a plus
• Technical expertise in one or more of: analysis of high-dimensional Omic data (scRNA-seq, spatial data, proteomics, metabolomics), population statistical genetics, or integrative multi-omics
• Primary author publications in scientific journals
• Programming skills in R and/or Python. Working knowledge of Linux/Unix and HPC clusters
• Knowledge and experience in Statistical and Machine Learning methods
• Strong communication skills with ability to present complex results to specialist and non-specialist audiences