Sr. Scientist - Computational Biology - Neuroscience & Rare Diseases

At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections, where you are valued, accepted and respected for who you are, allowing you to thrive both personally and professionally. This is how we aim to prevent, stop and cure diseases and ensure everyone has access to healthcare today and for generations to come.

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The Computational Sciences Centre of Excellence is a global organisation enabling Roche’s Research and Early Development units to develop novel therapeutics that will have an impact on patient lives. Within the Computational Sciences Centre of Excellence, the Computational Biology and Medicine department focuses on furthering our understanding of disease pathogenesis, patient populations, and target biology by having access to the largest Pharma R&D datasets in the world.

In partnership with our scientists across Roche, we create better medicines by augmenting every part of R&D through our data-driven culture.

We are seeking a highly motivated computational scientist to join our Neuroscience and Rare Diseases therapeutic area. In this role, you will be a key member of an interdisciplinary team dedicated to advancing our understanding of neurological diseases. As Roche continues to build and advance its capabilities in computational and data-driven R&D, this position offers an integral role in our strategy.

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. You will also be part of the wider Computational Biology and Medicine unit of the Computational Sciences Centre of Excellence drawing on the shared experience and expertise of colleagues globally.

• 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

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

• Contribute to a collaborative workplace culture of scientific rigor, continuous improvement, and open feedback
• Support the scientific growth of team members by sharing knowledge and expertise

You are a dedicated scientist with a strong background in applying computational methods to biological problems. You are motivated by scientific challenges and have a clear interest in translating data into meaningful biological insights.

• PhD in Bioinformatics, Biostatistics, Computational Biology, or a similar field with 3-5 years relevant work experience preferred.
• Demonstrated experience in drug discovery and/or translational research is highly valued
• Experience in disease biology is required; specific expertise in neurodegenerative diseases or neuro-immune interactions is a plus.
• Technical expertise in one or more of the following: analysis of high-dimensional Omic data (e.g., scRNA-seq, spatial data, proteomics, metabolomics), population statistical genetics, or integrative multi-omics from preclinical and/or clinical samples
• Evidenced scientific impact through primary author publications in scientific journals.
• Evidenced programming skills in R and/or Python. Working knowledge of a Linux/Unix environment and experience processing data on an HPC cluster
• Knowledge and experience in Statistical and Machine Learning methods
• Strong communication skills with the ability to present complex results clearly to both specialist and non-specialist audiences and the ability to work effectively in a collaborative, cross-functional scientific environment.

PhD in Bioinformatics, Biostatistics, Computational Biology, or a similar field, 3-5 years relevant work experience preferred, Experience in disease biology, Programming skills in R and/or Python, Working knowledge of a Linux/Unix environment and experience processing data on an HPC cluster, Knowledge and experience in Statistical and Machine Learning methods, Strong communication skills, Ability to work in a collaborative, cross-functional scientific environment