Day to Day Responsibilities:
• Serve as a Scientific Machine Learning (SciML) Scientist, bridging physics‑based modeling and modern deep learning to address complex manufacturing and engineering challenges.
• Develop hybrid modeling frameworks that integrate mechanistic solvers with data‑driven ML components, enabling robust, interpretable, and scalable SciML workflows.
• Build high‑performance AI surrogate models to accelerate numerical simulations (e.g., CFD, FEA), reducing computational turnaround time while preserving physical consistency.
• Provide technical leadership for SciML research initiatives supporting Corning RD&E, guiding projects from problem form...