Senior Scientist, Computational Materials Solutions

This is a fully remote position, open to applicants in Connecticut, +1 more state.

📋 Description

• Develop and implement molecular, statistical, computational, and chemistry-informed methodologies to explore material behavior, process mechanisms, and facilitate materials design.

• Assist MES product and technology development initiatives through AI/ML, predictive simulations, structure-property analysis, design-of-experiments support, optimization, and reusable computational workflows.

• Combine simulation data, experimental findings, and domain expertise to aid in hypothesis generation, experiment prioritization, and model-based interpretation of R&D outcomes.

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

• Convert computational results into actionable insights for MES scientists, engineers, and leadership.

• Create reusable solution libraries, workflows, documentation, and technical knowledge assets.

• Convey modeling assumptions, results, and insights effectively to both technical and non-technical stakeholders.

• Record methodologies and outcomes 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.

• Strong background in computational materials science, computational chemistry, molecular modeling, statistics, scientific computing, and simulation techniques.

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

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

• Familiarity with 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 collaborative, stakeholder-management, and communication abilities.

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

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

• Experience with design-of-experiments (DoE), optimization, or Bayesian methodologies.

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

• Publications, patents, or notable internal research contributions.

• Must not require Entegris immigration sponsorship now or in the future.

🏝️ Benefits

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

• Excellent health, dental, and vision insurance packages.

• Flexible work schedule.

• 11 paid holidays each year.

• Paid time off (PTO) policy.

• Education assistance.

• Values-driven culture with colleagues who prioritize People, Accountability, Creativity, and Excellence.