Scientist II, Modeling & Simulation at Entegris in Danbury, CT

  • Company: Entegris
  • Location: Danbury, CT
  • Salary: $95K – $120K
  • Job type: full time
  • Workplace: onsite
  • Posted: 2026-10-30

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Job description

Job Title: Scientist II, Modeling & Simulation Job Description: The Role Entegris is currently seeking a Scientist II, Modeling & Simulation to join our team. This position will be based in our Danbury, CT facility. As semiconductor technologies advance, new materials are becoming increasingly important to technology and product development. Our Modeling & Simulation team uses computational methods to better understand material properties, evaluate potential materials and formulations, and generate insights that support semiconductor technology development. In this role, you will contribute to atomistic, molecular, and data modeling and simulation activities by applying established computational methods, models, and tools. You will work closely with experienced team members and cross-functional partners to support modeling and simulation projects across a variety of materials and semiconductor applications. What You’ll Do Execute established atomistic, molecular, and data modeling and simulation methods to support material and technology development projects. Work with experienced team members and project stakeholders to understand technical problems and translate defined requirements into modeling and simulation activities. Apply established modeling approaches, including DFT, DFTB, Molecular Dynamics, and data modeling to generate technical insights and support project objectives. Generate DFT training sets to support the fine-tuning of Machine Learning Interatomic Potentials (MLIP) for Molecular Dynamics modeling and simulation. Support the evaluation and application of AI-based tools for material development. Analyze, document, and communicate modeling and simulation results to project team members and stakeholders. Follow established models, parameters, codes, procedures, calculations, and documentation practices to enable consistency and reuse of modeling approaches across similar applications. Contribute to improvements in modeling and simulation methods based on project results, feedback, and technical guidance. Collaborate with R&D staff, technologists, FAE, and other internal stakeholders on assigned modeling and simulation projects. What We Seek Strong communication and collaboration skills. Ability to work effectively with different stakeholders and within cross-functional teams. Basic understanding of semiconductor processes and/or materials. M.S. in Chemistry, Materials Science, Chemical Engineering, Physics, or a related field with a focus on computational chemistry, molecular dynamics, materials modeling, or a related discipline. Working knowledge of atomistic, molecular, or data modeling and simulation using commercial or open-source software. Familiarity with LINUX environments and one or more modeling and simulation tools such as LAMMPS, GROMACS, Quantum ESPRESSO, CP2K, VASP, xTB, or COSMO-RS/SAC. Exposure to or familiarity with AI/ML tools and approaches used in material development, such as ChemProp, MLIP, FM4M, AiZynthFinder, Transformers, message-passing approaches, or self-attention architectures. Working knowledge of Python or C/C++, with Python preferred, for computational modeling, data analysis, or AI/ML applications. Experience with molecular design, retrosynthesis, data modeling, or material informatics is a plus. Ability to collaborate with team members and stakeholders to understand project requirements and successfully execute assigned modeling and simulation work. Ability to apply established computational approaches and methods to technical problems. Delivery of accurate, high-quality modeling and simulation results within established project timelines. Ability to analyze results, identify issues, and make appropriate adjustments with guidance from more experienced team members. Willingness to learn new modeling, simulation, and AI/ML tools and approaches. Ability to apply modeling and simulation techniques across different materials, products, and processes. Commitment to continuous learning

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