Lead Scientist, Modeling & Simulation

The Role: 

Entegris is currently seeking a Modeling & Simulation (M&S) Engineer to join our Digital Solutions Enablement team. In this role, you will perform simulations of products and product derivatives using established models. You will interpret the results and validate model predictions against empirical data. You will then deploy validated models for business users through AI-enabled tools and standard operating procedures (SOPs), supported by training and first-line application support. You will also work with business unit R&D teams and the Core M&S Team to translate scientific and engineering challenges into clear modeling requirements and fit-for-purpose solutions. 

What You’ll Do: 

• Perform simulations. Apply established models to conduct multiphysics simulations, computational fluid dynamics (CFD), finite element analysis (FEA), involving fluid flow, heat transfer, structural mechanics, and design for products and product derivatives. 

• Analyze and interpret results. Evaluate simulation results, communicate key findings, and identify opportunities to improve existing products and designs. 

• Deploy models and workflows. Make standardized M&S capabilities accessible to R&D users through AI-enabled tools and standard procedures to help them to address technical challenges. 

• Validate simulations. Use simulation results to validate models against empirical data and improve prediction.

• Translate R&D needs into modeling requests. Partner with business unit R&D teams to understand technical challenges and define executable M&S requests with clear inputs, assumptions, and expected outputs. 

• Train and support users. Develop application guidance, deliver training, and provide first-line support so researchers can use models and workflows effectively. 

• Connect user needs with core development. Capture unmet needs, recurring issues, and application gaps, and provide actionable feedback to the Core M&S Team. 

• Contribute to AI/Digital Scientists. Collaborate with modeling specialists and R&D users to develop AI-enabled tools that support scientific and engineering workflows. 

What We Seek: 

Minimum Qualifications 

• Master’s degree in mechanical engineering, chemical engineering, aerospace engineering, or a related engineering field 

• Five years of relevant industry experience 

• Strong knowledge of fluid dynamics, heat transfer, engineering design, and numerical modeling 

• Three years of experience using commercial simulation software, such as Ansys, Abaqus, or COMSOL, or open-source software, such as OpenFOAM 

• Proficiency with CAD software, such as SolidWorks or Creo, including geometry preparation for simulation 

• Experience using high-performance computing (HPC) clusters and scaling simulations in cloud environments 

• Experience applying modeling and simulation to scientific or engineering problems and translating R&D questions into clearly defined modeling requirements 

• Experience validating models and collaborating with product development or laboratory teams to define and obtain relevant experimental data 

• Ability to deploy established models and workflows for researchers with varying levels of modeling experience 

• Experience training technical users and troubleshooting modeling or scientific application issues 

• Strong written and verbal communication skills and the ability to collaborate across R&D teams and with modeling specialists 

• Ability to identify limitations in existing tools, capture user needs, and communicate actionable recommendations to guide future development 

Preferred Qualifications 

• Industry experience in the semiconductor, aerospace, or oil and gas sectors 

• Experience with manufacturing process simulation, including blow molding or injection molding 

• Experience automating simulation or engineering workflows using Python, MATLAB, or C++ 

• Familiarity with AI-enabled scientific workflows or experience contributing to AI/Digital Scientist development 

Outstanding Candidates Will Have: 

• A track record of enabling R&D teams outside specialist modeling groups to adopt standardized modeling workflows 

• Hands-on experience developing AI assistants or agents for scientific or engineering applications 

• Demonstrated success converting recurring user questions and unmet needs into improvements to models, tools, or scientific workflows 

• A strong commitment to simulation-driven design and continuous technical learning 

• Demonstrated commitment to the company’s long-term success and the ability to tackle complex challenges 

• Exemplifies Entegris’ core values: Integrity, Innovation, Teamwork, and Dedication to Excellence