Senior Scientist, Computational Materials Solutions

Entegris • Danbury, CT

5d • Remote

About The Position

Entegris is currently seeking a Senior Scientist, Computational Materials Solutions to join our Digital Innovation Team in the Technology and Innovation organization within our Materials Solutions (MS) business. This position will be remote. This role focuses on accelerating innovation by combining computational science, machine learning, and domain expertise to deepen scientific understanding, guide experimentation, and translate research breakthroughs into scalable technologies for the Molecular & Engineering Solutions (MES) business unit. You will translate MES business and technology priorities into actionable computational approaches, including molecular and materials modeling, predictive simulation, statistical and hybrid methods, and scientific data analysis. You will work in close partnership with experimental scientists, engineers, R&D leaders, and cross-functional technology teams to develop solutions that inform materials design, process development, product performance, and next generation technologies. The ideal candidate brings deep quantitative rigor, curiosity-driven problem solving, and the ability to bridge theory, data, and experimentation.

Requirements

• M.S. or Ph.D. in Chemistry, Materials Science, Physics, Engineering, or related scientific discipline.
• Strong foundation in computational materials science, computational chemistry, molecular modeling, statistics, scientific computing, and simulation
• Experience supporting research, experimentation, or early-stage technology development.
• Ability to connect computational results to physical or chemical mechanisms and translate those results into practical R&D decisions.
• Working knowledge of model verification, validation, uncertainty quantification, documentation, simulation data management, model reuse, and lifecycle governance.
• Hands-on experience developing computational, simulation, or data-driven solutions using Python and scientific libraries such as NumPy, pandas, scikit-learn, PyTorch , TensorFlow, or related tools.
• Strong collaboration, stakeholder-management, and communication skills with the ability to present complex technical work clearly to scientific, engineering, and business audiences.

Nice To Haves

• 1-3 years of experience in materials science, chemistry, semiconductor, life sciences, energy, or advanced manufacturing R&D.
• Demonstrated success combining experimental data with modeling and AI to guide discovery or development.
• Experience with design-of-experiments (DoE), optimization, or Bayesian methods.
• Familiarity with visualization, notebooks, or technical storytelling for R&D audiences.
• Publications, patents, or significant internal research contributions.

Responsibilities

• Develop and apply molecular, statistical and computational, chemistry-informed solutions to investigate material behavior, process mechanisms, and guide materials design.
• Support MES product and technology development programs through AI/ML, predictive simulations, structure-property analysis, design-of-experiments support, optimization, and reusable computational workflows.
• Integrate simulation data, experimental results, and domain knowledge to support hypothesis generation, experiment prioritization, and model-based interpretation of R&D results.
• Perform model calibration, verification, validation, sensitivity analysis, and uncertainty quantification to build scientific confidence in computational recommendations.
• Translate computational outputs into actionable guidance for MES scientists, engineers, and leaders, including clear communication of assumptions, limitations, uncertainty, and decision implications.
• Build reusable solution libraries, workflows, documentation, and technical knowledge assets that can be applied across MES priorities and broader Materials Division R&D needs.
• Communicate modeling assumptions, results, and insights clearly to technical and non-technical stakeholders.
• Document methods and results in technical reports, internal publications, and knowledge repositories.

Benefits

• Compensation: $100,500 - $125,500 per year range with actual pay dependent on candidate overall skills for the role
• Generous 401(K) plan with an impressive employer match
• Excellent health, dental and vision insurance packages to fit your needs
• Flexible work schedule and 11 paid holidays a year
• Paid time off (PTO) policy that empowers you to take the time you need to recharge
• Education assistance to support your learning journey
• Values-driven culture with colleagues that rally around People, Accountability, Creativity and Excellence

What This Job Offers

• Job Type: Full-time
• Career Level: Senior