Experience with gnn and transformers architectures
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Eli Lilly is seeking a Research Advisor/Sr. Advisor for their AI for Science team, focusing on the intersection of AI/ML, Chemistry, and Biology to advance drug discovery. The ideal candidate will possess a PhD in a relevant scientific field, experience in machine learning frameworks, and a track record of innovation in science.
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Job Summary
The role involves pioneering state-of-the-art technologies at the intersection of AI, Chemistry, and Biology to fundamentally change drug discovery.
Candidates will lead the development of scientific foundation models that integrate molecular design and biological data to support decision-making across the pipeline.
Lilly offers a comprehensive benefit program including medical, dental, vision, 401(k), pension, and well-being benefits alongside a competitive salary range.
Matching Summary
Match Score: 75
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Eli Lilly is seeking a Research Advisor/Sr. Advisor for their AI for Science team, focusing on the intersection of AI/ML, Chemistry, and Biology to advance drug discovery. The ideal candidate will possess a PhD in a relevant scientific field, experience in machine learning frameworks, and a track record of innovation in science.
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Salary
Base: $151,500 - $244,200; Bonus/Equity: Eligible for company bonus based on performance; Benefits: Comprehensive program including 401(k), pension, medical, dental, vision, and wellness perks
Skills & Requirements
Must-have
PhD in Computer Science or related field
First-author publications in high-impact venues
Experience with GNN and Transformers architectures
Modern AI/ML frameworks for molecular data
Nice-to-have
Ability to translate chemistry problems into ML formulations
Collaboration experience with lab scientists
MLOps and Data Engineering partnership skills
Interest in publishing at top-tier venues
Key Requirements
PhD in Computer Science, Machine Learning, Statistics, Computational Chemistry, Computational Biology, Physics, or Scientific field
Innovation evidenced by first-author publications in high-impact journals or top-tier ML conferences