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Natalie Eyke, Ph.D., is a Chemical Engineering Senior Scientist at Vertex Pharmaceuticals, specializing in applied machine learning to enhance pharmaceutical processes. At Vertex, key contributions include developing a Bayesian optimization workflow, optimizing synthetic procedures, and managing technology transfers for cGMP manufacturing. Previously, at the Massachusetts Institute of Technology, Natalie conducted research on integrating machine learning and high-throughput experimentation while supervising graduate and undergraduate students. Experience at Merck involved designing processes for an FDA-approved drug and conducting extensive experimentation to maximize yield and purity. Educational qualifications include a Ph.D. in Chemical Engineering from MIT and a Bachelor of Engineering from the University of Michigan.