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# Modeling Scientist

- **Company:** Novelis Inc.
- **Location:** Kennesaw, GA, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Abaqus, Microsoft Azure, Computational Fluid Dynamics, Computer Simulation, Computer Programming, Comsol Multiphysics, Python (Programming Language), Machine Learning, SQL Databases, Management of Software Versions, Web Applications, Cloud Platform System, Feature Engineering, Data Ingestion, Model Validation, Machine Learning Operations, Ansys, Ls-dyna
- **Published:** October 26, 2026
- **Apply:** https://www.adzuna.com/details/5702592749

## About the Role

* PhD in metallurgy, metallurgical engineering, materials science/engineering or mechanical engineering.
 * Minimum experience of 2+ years in multiscale, multiphysics modeling and application of machine learning after PhD completion gained in industrial R&D or in partnership with industry.
 * Candidates will have experience in the use of LS-DYNA, Abaqus, ANSYS, COMSOL or other well-known commercial FE software, as well as in some of the following:
 + Large scale crystal plasticity modeling, e.g., CPFEM, DAMASK, VPSC.
 + Multiphysics modeling e.g., fully and sequentially coupled thermo - electro - mechanical - magnetic analysis and computational fluid dynamics.
 + FE Pre/post processors, user subroutines.
 * Strong foundation in statistical modeling, machine learning algorithms, and model evaluation techniques and application to materials modeling.
 * Strong programming skills in Python; experience with SQL, data-intensive systems, and cloud systems (e.g. Microsoft Azure)
 * Demonstrated experience building ML workflows, pipelines and web applications or interactive dashboards
 * Technical leadership experience in R&D with demonstration of good project management skills.
 * Broad science and engineering background and ability to connect knowledge across multiple disciplines.
 * Capability to thrive in a team environment, communicate well, and to engage and influence wide variety of stakeholders throughout the organization.
 * International outlook and desire to travel to other Novelis or customer locations., * Applicants are particularly sought who combine strong modeling capabilities with specialized capabilities in the following areas:
 + Mechanical behavior of metals, in particular forming, texture evolution, damage and fracture of aluminum alloys;
 + Metallurgy of aluminum alloys;
 + Use of experiments to validate models and analysis of the data;
 + Advanced models for the mechanical behavior of metallic materials and their use in FE simulations.
 * Direct or collaborative experience in experimental validation of computational models
 * Experience designing or implementing agnetic AI systems

Please note that we are unable to provide visa sponsorship for this position. Candidates must be legally authorized to work in the United States without the need for current or future sponsorship.

## Description

* Act as company-wide subject matter expert for multiscale, multiphysics modeling and application of machine learning to materials modeling in support of global R&D projects.
 * Establish advanced materials and data driven models to develop capabilities that will guide and accelerate development of transformational and sustainable products and processes.
 * Design, develop, and validate statistical and machine learning models for prediction, optimization, and simulation
 * Build end-to-end ML workflows and pipelines, including data ingestion, feature engineering, training, evaluation, versioning, and deployment
 * Define and lead modeling driven projects to address critical product and process development challenges.
 * Partner with wide range of internal specialists to develop solutions e.g., with product metallurgists, rolling process engineers, formability, surface, corrosion and computational material scientists.
 * Establish and lead supporting partnerships with universities, national labs and other external organizations.
 * Support wider adoption and application of both physics and data driven modeling tools amongst other specialists.
 * Collaborate with colleagues to develop associated experimental programs that provide supporting data or understanding critical to model development.