Senior Principal Machine Learning Scientist, AI Biology & Translation (AIBT)

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Company Overview

A leading global healthcare and pharmaceutical organization is advancing drug discovery and development through artificial intelligence, data science, and computational sciences. Its research and early development teams are leveraging large-scale biological data and advanced computational models to accelerate scientific discovery and develop more innovative medicines.

The organization has established a unified Computational Sciences Center of Excellence to harness the transformative potential of data and artificial intelligence and support scientists across research and development programs worldwide.

The AI Biology & Translation (AIBT) department is developing next-generation AI systems for biology. Its work focuses on building AI models that learn from biological data at unprecedented scale to generate new insights into disease mechanisms, therapeutic opportunities, and human biology.

The organization is seeking an exceptional scientist to lead a research program focused on Genomics AI and Biological Foundation Models. This role is suited to a researcher with a strong background in machine learning, sequence modeling, regulatory genomics, and representation learning who is passionate about advancing AI applications in biology.

As a Senior Principal Scientist, the successful candidate will lead a team developing AI models that learn from genomic sequences, gene regulation, cellular states, perturbational biology, and multimodal biological data. The role will also contribute to defining the organization’s strategy for applying modern machine learning to biological discovery and establishing capabilities that accelerate therapeutic innovation across its research and development portfolio.

Key Responsibilities

• Lead the scientific roadmap and strategy for genomics foundation models designed to accelerate therapeutic innovation.
• Develop state-of-the-art sequence modeling, self-supervised learning, and generative AI models using multimodal biological data.
• Work with experimental research teams to translate machine learning innovations into insights for target discovery and disease understanding.
• Serve as a scientific leader within the AI Biology & Translation department and influence the organization’s long-term AI-for-biology strategy.
• Publish novel scientific research in leading machine learning, artificial intelligence, and genomics venues.
• Represent the organization at international scientific conferences and industry events.
• Evaluate emerging machine learning technologies and identify opportunities for transformative scientific impact.
• Lead, mentor, and develop a team of scientists while fostering innovation, scientific excellence, and collaboration.
• Collaborate across computational and experimental disciplines to advance biological discovery.
• Contribute to the development of new computational capabilities that support therapeutic research and development.

Required Qualifications

• PhD in Computer Science, Machine Learning, Computational Biology, Physics, or another related quantitative discipline.
• At least 7 years of post-PhD research experience developing innovative AI and machine learning methods for biological discovery.
• Deep expertise in foundation models, sequence modeling, self-supervised learning, generative AI, multimodal machine learning, or related areas.
• Strong expertise in gene regulation, epigenomics, functional genomics, regulatory biology, or cellular systems biology.
• Strong record of publishing novel computational methods in leading AI, machine learning, or genomics venues.
• Demonstrated ability to lead complex scientific initiatives and influence multidisciplinary teams.
• Recognized contributions to the field through influential publications, open-source software, invited presentations, patents, or other significant scientific achievements.
• Strong scientific communication and collaboration skills.
• Demonstrated ability to mentor and develop scientific talent.

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