Sr. Scientist - Computational & Applied AI

The Senior Computational and Applied AI Scientist within the Computational Biology and Medicine team is responsible for developing and deploying translational and applied AI frameworks to accelerate our Immunology and Cardiovascular, Renal, and Metabolism (CVRM) portfolios. Operating at the final stage of translational execution for Discovery and Early Development, you will focus on moving beyond pure statistical correlation toward a systems-level, mechanistic understanding of disease and target biology. This position offers a trajectory of professional development aligned with scientific excellence and modern enterprise productivity frameworks ensuring our computational pipelines directly optimize R&D throughput and compress discovery cycles.

• Working across departments to co-develop and implement advanced machine learning models focused on explainable and causal AI methods (such as causal models, symbolic regression, and counterfactual inference) to map disease pathways and unlock true mechanistic target validation.
• Adaptation and fine-tune state-of-the-art biological foundation models to predict novel therapeutic targets in complex immune diseases and CVRM.
• Bridging the translational gap by implementing adversarial domain adaptation and cross-species translation algorithms to dynamically align animal model phenotypes with human patient endotypes.
• Leveraging patient-level multi-omics, spatial profiles, and real-world clinical datasets to identify distinct disease endotypes, defining mechanistic patient selection criteria that enable clinical scientists to stratify responder vs. non-responder populations.
• Constructing dynamic representations and physics-informed models (e.g., Neural ODEs, PINNs) to capture physiological kinetics, temporal disease progression, and patient "digital twins" entirely in silico.
• Applying graph-based deep learning approaches, building and querying large-scale biological knowledge graphs to capture systems-level interactions across complex tissue-remodeling and auto-inflammatory networks.
• Anchoring the final stage of the organizational continuum, translating algorithmic innovations and "ML-ready" frameworks directly into high-value portfolio deliverables.
• Collaborating cross-functionally with clinical scientists, wet-lab disease biology experts, biostatisticians, and enterprise engineers across pRED and gRED to convert ambiguous therapeutic questions into concrete computational pipelines.
• Ensuring provenance and explainability is an integral feature of your insight delivery to stakeholders

• You hold a PhD (preferred) or MSc in Computational Biology, Computer Science, Machine Learning, Bioinformatics, Systems Biology, Artificial Intelligence, or a highly quantitative field.
• You bring 3+ years (Senior Scientist) or 6+ years (Principal Scientist) of post-doctoral or biopharmaceutical industry experience delivering applied AI and data science solutions in a drug-discovery setting.
• You possess hands-on experience applying causal inference toolkits, graph neural networks, or generative models to high-dimensional biomedical data (single-cell, spatial omics, or clinical trial datasets).
• You possess experience adapting large-scale biological foundation models or building dynamic systems models to capture temporal disease progression.
• You demonstrate an active interest or deep domain understanding of human immunology, complex and multifactorial diseases, or system-level pathophysiology.
• You exhibit elite communication and teamwork skills, with a proven track record of acting as a cross-functional catalyst between pure computational engineers and wet-lab experimentalists.

This position is based in Basel, Switzerland