Senior Scientist, Computational Materials Solutions

This is a fully remote position, open to applicants in Pennsylvania.

📋 Description

• Drive innovation by merging computational science, machine learning, and domain expertise for the Materials Solutions sector.

• Convert business and technological priorities into computational methodologies, including molecular and materials modeling, predictive simulations, statistical and hybrid approaches, and scientific data analysis.

• Create and implement solutions informed by computational chemistry to explore material behavior, process mechanisms, and materials development.

• Aid in product and technology advancement through AI/ML, predictive simulations, structure-property analysis, design-of-experiments support, optimization, and reusable computational workflows.

• Synthesize simulation data, experimental findings, and domain knowledge to formulate hypotheses, prioritize experiments, and analyze R&D outcomes.

• Conduct model calibration, verification, validation, sensitivity analysis, and uncertainty quantification.

• Convert computational results into actionable recommendations for scientists, engineers, and leaders.

• Develop reusable solution libraries, workflows, documentation, and technical knowledge resources.

• Articulate modeling assumptions, results, and insights to both technical and non-technical audiences.

• Record methods and results in technical reports, internal publications, and knowledge repositories.

⛳️ Requirements

• M.S. or Ph.D. in Chemistry, Materials Science, Physics, Engineering, or a related scientific field.

• Solid foundation in computational materials science, computational chemistry, molecular modeling, statistics, scientific computing, and simulation.

• Experience in supporting research, experimentation, or early-stage technology development.

• Capability to link computational outputs to physical or chemical mechanisms and translate them into actionable R&D decisions.

• Proficient understanding of model verification, validation, uncertainty quantification, documentation, simulation data management, model reuse, and lifecycle governance.

• Practical experience in developing computational, simulation, or data-driven solutions using Python and scientific libraries such as NumPy, pandas, scikit-learn, PyTorch, TensorFlow, or similar tools.

• Strong teamwork, stakeholder management, and communication abilities.

• 1–3 years of experience in materials science, chemistry, semiconductor, life sciences, energy, or advanced manufacturing R&D.

• Proven success in integrating experimental data with modeling and AI to facilitate discovery or development.

• Familiarity with design-of-experiments (DoE), optimization, or Bayesian methods.

• Knowledge of visualization, notebooks, or technical storytelling for R&D audiences.

• Publications, patents, or notable internal research contributions.

• Entegris does not provide immigration-related sponsorship; applicants must not require Entegris immigration sponsorship now or in the future.

🏝️ Benefits

• Generous 401(K) plan with an exceptional employer match.

• Comprehensive health, dental, and vision insurance packages tailored to your needs.

• Flexible work schedule.

• 11 paid holidays each year.

• Paid time off (PTO) policy that encourages you to take the time needed to recharge.

• Educational assistance to support your learning journey.

• Values-driven culture with colleagues who are committed to People, Accountability, Creativity, and Excellence.