Overview In this role you will advance multiscale, physics-guided materials modeling to accelerate the development of sustainable aluminum products and processes. You will bridge microstructure, thermomechanical processing, and product performance using physics-based and data-driven approaches, working with metallurgists, engineers, and customers. Your hands-on work will combine modeling with experimental data from Novelis labs and pilot facilities, with opportunities to collaborate globally. This position offers visibility, multidisciplinary collaboration, and potential to shape Novelis' materials research and product solutions.
Compensation / Benefits- Medical, dental and vision insurance
- Health Savings Account (HSA) and Health Reimbursement Account (HRA)
- Flexible Spending Account (FSA)
- Company-paid life insurance and voluntary options
- Paid vacation and PTO
- 401(k) with company match
Responsibilities- Serve as a company-wide subject matter expert for multiscale, multiphysics modeling and ML in materials modeling for global R&D projects
- Develop advanced materials and data-driven models to accelerate transformational product and process development
- Design, develop and validate statistical and ML models for prediction, optimization, and simulation
- Build end-to-end ML workflows including data ingestion, feature engineering, training, evaluation, versioning, and deployment
- Lead modeling-driven projects addressing critical product and process challenges
- Collaborate with product metallurgists, rolling/process engineers, formability, surface, corrosion scientists; support external partnerships
- Foster adoption of physics and data-driven modeling tools across the organization
- Coordinate with experimental programs to provide data for model development
- Travel and collaborate with internal and external partners to impact global business
- Provide leadership in multidisciplinary teams integrating modeling with experimental work
Key requirements- PhD in metallurgy, metallurgical engineering, materials science/engineering or mechanical engineering
- 2+ years of post-PhD experience in multiscale, multiphysics modeling and ML in industrial R&D or industry partnership
- Experience with FE software (LS-DYNA, Abaqus, ANSYS, COMSOL) and with crystal plasticity modeling (CPFEM, DAMASK, VPSC)
- Experience in multiphysics (thermo-electro-mechanical-magnetic, CFD) modeling and FE preprocessing/postprocessing
- Strong statistical modeling, ML, and model evaluation skills; solid Python programming; SQL and cloud experience (e.g., Azure)
- Proven ability to build ML workflows, pipelines, and web apps or dashboards
- Technical leadership and project management experience in R&D
- Broad, interdisciplinary engineering background with strong communication and stakeholder influence
- Willingness to travel internationally
- team collaboration
- strong communication
- stakeholder influence
- LS-DYNA
- Abaqus
- ANSYS
