Principal Scientist, Integrated Computational and Experimental Inflammation Discovery

What You Will Do

Let’s do this. Let’s change the world. In this vital role you will combine experimental and computational strategies to accelerate discovery and development of innovative therapies. You will bring deep expertise across wet-lab biology and AI/ML-driven computational and agentic research approaches, enabling human-data-driven understanding of disease mechanisms and therapeutic opportunities.

Key Responsibilities

• Continuously apply computational, agentic and other AI-driven approaches to generate mechanistic insights, refine therapeutic hypotheses, and guide experimental design.
• Design, execute, analyze, and interpret studies to investigate disease mechanisms and test therapeutic hypotheses.
• Generate high-quality experimental data to support target identification, validation, and progression of Inflammation research programs.
• Integrate experimental findings with published literature, human genetics, clinical observations, and other data sources to develop mechanistic insights and inform scientific decision-making.
• Participate in scientific discussions, target reviews, and portfolio evaluations by contributing data-driven insights and recommendations.
• Present scientific findings and recommendations to project teams, governance forums, and departmental meetings.
• Maintain accurate documentation and contribute to organizational knowledge-sharing efforts.
• Embrace and contribute to a culture of scientific curiosity, collaboration, continuous learning, and operational excellence.

Basic Qualifications

• Doctorate degree PhD OR PharmD OR MD [and relevant post-doc where applicable] and 2 years of Industry experience in Inflammation/Immunology research
• Bachelor’s degree and 7 years of Industry experience in Inflammation/Immunology research

Preferred Qualifications

• Experience working effectively within highly collaborative and matrixed research environments.
• Ability to balance scientific rigor with urgency and adaptability in a dynamic research environment.
• Demonstrated commitment to teamwork, knowledge sharing, and continuous improvement.