Lead - Process Modeling Engineer

Job description

Develop physics-based feature-scale models of plasma deposition using SEMulator3D®, incorporating key physical mechanisms into the models Analyze simulation outputs and compare predicted results with experimental measurements in partnership with process engineering teams Identify gaps or mismatches between simulated and experimental trends and propose model refinements Prepare clear visualizations, summaries, and technical documentation to communicate modeling results and insights Apply ML methods (RSM, Gaussian Processes, Neural Nets, Bayesian optimization) to create fast predictive guidance for experiments Work closely with process engineers to validate and guide both simulations and ML predictions for their customer demos Participate in technical discussions and design reviews to improve methodology and modeling best practices Contribute to internal knowledge sharing by documenting learnings, challenges, and recommended modeling strategies Master's or PhD in Chemical Engineering, Materials Science, Chemistry or Physics or related field Basic understanding and working knowledge of plasma-based Semiconductor deposition processes such as Plasma Enhanced Atomic Layer Deposition (PEALD), Plasma Enhanced Chemical Vapor Deposition (PECVD) and Physical Vapor Deposition (PVD) Experience with scientific programming or data analysis tools (e.g., Python, MATLAB) Ability to connect modeling outputs with experimental process engineering Experience with scientific programming or data analysis tools (e.g., Python, MATLAB) Ability to connect modeling outputs with experimental process engineering In-depth understanding of process development for plasma deposition/etch products, process modeling, or virtual fabrication Established skills in building AI/ML models using simulation data Exposure to SEM, TEM, EDS, or metrology data interpretation Basic understanding of feature-scale or reactor-scale simulations Familiarity with software product development methodologies