Computational Materials Scientist
- Apply advanced modeling to accelerate materials discovery and development and enable in-silico materials design
- Investigate physical processes and mechanisms across multiple length and time scales.
- Collaborate closely with experimentalists and other modeling experts to validate and improve models.
- Develop and deploy computational models that address business needs and enhance research workflows.
- Ph.D. in Materials Science and Engineering, Chemical Engineering, Chemistry, Physics, Computational Science, or related fields.
- Minimum 3 years of research experience in materials modeling (including Ph.D. research).
- Proven experience in modeling and simulating behavior of complex materials such as semicrystalline polymers, hydrocarbons, soft matter, complex fluids, and composites.
- Proficiency in atomistic simulations, Density Functional Theory, molecular dynamics, Monte Carlo, coarse-grained methods, and/or finite element analysis.
- Expertise in multiscale and multi-physics modeling, including techniques from ab-initio to continuum methods across a broad range of time and length scales.
- Experience with hybrid modeling and integrating physics-based and data-driven methods (e.g., machine learning)
- Experience with forcefield development and MLIPs (Machine Learning Interatomic Potentials).
- Experience with both CPU and GPU high-performance computing.
- Strong programming skills (Python, C++, scripting for automation).
- Excellent communication and collaboration skills across multidisciplinary teams.
- Polymer physics, soft matter physics, fluid mechanics
- Thermodynamics, statistical mechanics, interface science, and kinetic modeling
- Machine learning, statistical modeling, materials informatics
- Experience in energy and sustainability-related materials
Req ID: 83024 Nearest Major Market: Houston
Job Segment: Sustainability, Chemical Engineer, Informatics, Scientific, Energy, Research, Engineering, Technology
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