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Intern Computational Materials Science Jobs in Georgia

D.) in Materials Science, Mechanical Engineering, or a related field, with more than ten years of experience in computational modeling. * Expertise in metallurgy and materials science, as well as ...

Intern

Riceboro, GA · On-site

$13.50 - $18/hr

The Laboratory Intern will support the Application Laboratory team with testing, data collection ... Science, Materials Science, or a related technical field. * Strong attention to detail and ...

The Laboratory Intern will support the Application Laboratory team with testing, data collection ... Science, Materials Science, or a related technical field. Strong attention to detail and ...

... and computational material scientists. * Establish and lead supporting partnerships with ... PhD in metallurgy, metallurgical engineering, materials science/engineering or mechanical ...

... and computational material scientists. * Establish and lead supporting partnerships with ... PhD in metallurgy, metallurgical engineering, materials science/engineering or mechanical ...

Lab Intern

Atlanta, GA

$14.50 - $19.25/hr

Chemistry, Chemical Engineering and Materials Sciences majors are preferred, but others will be considered. Additional Information Each intern will be paid $1,000/month to complete a scope of ...

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Intern Computational Materials Science information

What is the difference between Intern Computational Materials Science vs Intern Materials Engineering?

AspectIntern Computational Materials ScienceIntern Materials Engineering
Required CredentialsUndergraduate or graduate in materials science, physics, or related fields; basic programming skillsUndergraduate or graduate in materials engineering, mechanical engineering, or related fields; foundational technical knowledge
Work EnvironmentResearch labs, computational modeling, data analysisDesign, testing, and development in labs or manufacturing settings
Industry UsageResearch institutions, tech companies, aerospace, academiaManufacturing firms, product development, construction

Intern Computational Materials Science focuses on computational modeling and simulations of materials properties, while Intern Materials Engineering emphasizes practical design, testing, and application of materials. Both roles require a background in materials-related fields but differ in their core activities and work environments.

What does an intern in computational materials science do?

An Intern in Computational Materials Science assists in research and development by applying computational techniques to study and predict the properties and behaviors of materials. Typical tasks include running simulations, analyzing data, and working with software tools to model materials at the atomic or molecular level. Interns may collaborate with researchers to design experiments, interpret results, and contribute to scientific publications or reports. This role provides hands-on experience in both computational methods and materials science, helping to bridge theory and practical application.

What are the key skills and qualifications needed to thrive as an intern in computational materials science, and why are they important?

To thrive as an Intern in Computational Materials Science, you need a solid background in materials science, physics, or engineering, along with coursework in computational modeling and data analysis. Familiarity with programming languages like Python or MATLAB, experience with simulation software (such as VASP or LAMMPS), and knowledge of high-performance computing are typically required. Strong analytical thinking, attention to detail, and effective teamwork are important soft skills for success in collaborative research environments. These skills enable interns to contribute meaningfully to research projects, analyze complex materials data, and communicate findings clearly within multidisciplinary teams.

What types of projects can an intern in computational materials science expect to work on during their internship?

As an Intern in Computational Materials Science, you can expect to engage in projects involving simulations of material properties, data analysis from computational experiments, and the development of models to predict material behavior. You may collaborate with researchers and senior scientists to support ongoing investigations or help optimize simulation workflows. These projects often require proficiency in programming languages such as Python or MATLAB and may involve the use of specialized software like VASP or LAMMPS. The experience provides a hands-on understanding of how computational methods contribute to advancing materials research and often includes opportunities to present your findings to the team.
What are the most commonly searched types of Computational Materials Science jobs in Georgia? The most popular types of Computational Materials Science jobs in Georgia are:
Infographic showing various Intern Computational Materials Science job openings in Georgia as of August 2026, with employment types broken down into 18% Internship, 51% Full Time, 25% Part Time, and 6% Temporary. Highlights an 76% In-person, 6% Hybrid, and 18% Remote job distribution.

Lead Modeling Scientist

Novelis

Kennesaw, GA

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 15 days ago


Novelis rating

7.5

Company rating: 7.5 out of 10

Based on 56 frontline employees who took The Breakroom Quiz

259th of 537 rated manufacturers


Job description

Novelis is one of the world leaders in aluminum recycling and rolling and a leading sustainable aluminum solutions provider. Driven by our purpose of shaping a sustainable world together, we work alongside our customers to provide innovative solutions to the aerospace, automotive, beverage packaging and specialty markets. Headquartered in Atlanta, Georgia, Novelis has approximately 13,000 employees in 32 operating facilities on 4 continents.


The Lead Modeling Scientist has a key role in advancing Novelis’ capabilities in computational modeling, with the primary objective of linking aluminum sheet process conditions, microstructure and texture evolution, and material properties. This work will support faster product innovation across various markets in which Novelis operates, as well as improved plant performance. The role requires an unique combination of deep expertise in metallurgy and materials science, coupled with advanced modeling proficiency.

The position focuses on predictive modeling, which is integrated with experimental validation and data analytics to optimize manufacturing processes for aluminum products. As a key member of Novelis’ Americas R&D organization, the Lead Modeling Scientist will spearhead the development and deployment of multi-physics, multi-scale materials modeling and physics-guided AI modeling capabilities. These efforts are critical for accelerating the development of sustainable products and processes.

Central to the role is bridging microstructural length scales as applied to Novelis’ products—including sheet and plate—and to the company’s manufacturing processes such as casting, rolling, and heat treatments. The position will also focus on developing a deeper understanding of the relationships among alloy chemistry, thermomechanical processing, microstructure, properties, and overall product performance.

Responsibilities:
  • Develop and maintain Integrated Computational Materials Engineering (ICME) models that connect process parameters, microstructure, and properties for flat aluminum sheet products, including processes such as homogenization, heat treatment, precipitation, recrystallization, texture development and grain growth.
  • Design and implement multi-scale models to link process parameters with microstructure and properties for casting, rolling, heat treatment, coating, CASH, batch annealing and related processes relative to Flat Rolled Aluminum Products.
  • Constitutive behavior models: Flow stress, work hardening, strain rate sensitivity
  • Formability & failure prediction models: FLD, FLC, earing, spring-back, bendability
  • Create and refine process simulation tools using methods such as finite element, finite difference, cellular automata, and phase-field modeling to predict thermal and mechanical behavior.
  • Integrate modeling results with experimental characterization techniques (including SEM, EBSD, XRD, DSC) and plant data to validate predictions and continually improve model accuracy.
  • Build thermodynamic and kinetic models using tools like Thermo-Calc, DICTRA, TC-Prisma, and Pandat to support alloy design and process optimization.
  • Lead end-to-end modeling projects, from scoping and model development through validation and deployment, with the goal of improving or innovating aluminum sheet products and processes across beverage packaging, automotive, specialties, and aerospace markets.
  • Automate workflows for predicting microstructure-property relationships and incorporate feedback from plant trials to enhance model robustness.
  • Collaborate with plant engineers and R&D teams to apply models for troubleshooting and improving productivity, recovery, and quality.
  • Document methodologies and results in technical reports and contribute to intellectual property through invention disclosures and patents.
Required Qualifications
  • Advanced degree (M.S. or Ph.D.) in Materials Science, Mechanical Engineering, or a related field, with more than ten years of experience in computational modeling.
  • Expertise in metallurgy and materials science, as well as process and microstructure modeling for metallic systems, especially aluminum alloys. Flat rolled aluminum products experience is largely preferred
  • Proficiency in modeling software such as Thermo-Calc, DICTRA, TC-Prisma, and Pandat, and in numerical methods including finite element, finite difference, cellular automata, and phase-field modeling.
  • Programming skills in MATLAB, FORTRAN, and C/C++, along with proficiency in statistical analysis tools like JMP and R.
  • Strong understanding of metallurgical principles and characterization techniques.
  • Excellent technical communication and project management skills.
  • Proven track record of solving plant issues through modeling with measurable business impact.
  • Experience deploying predictive models in production environments to improve throughput and quality.
Preferred Qualifications
  • Machine Learning for materials: Property prediction, Process window optimization, Defect classification
  • Digital twin development: End-to-end process-to-property simulation
  • High-performance computing (HPC): Parallel simulations, cloud computing
  • Data pipelines & model deployment: MLOps, version control, model governance
  • DOE (Design of Experiments)
  • Multi-variable regression & sensitivity analysis
  • Model calibration & uncertainty quantification

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

What We Offer:

Novelis benefits say a lot about how we care for each other. Our employees and their families have many different needs. As a result, our benefits offer choices on many levels and are high in quality, competitive in the marketplace, and affordable. These are a few of the benefits we offer to support you and your family’s well-being:

  • Medical, dental and vision insurance
  • Health savings accounts – Company Funded Health Savings Account (HSA) and Health Reimbursement Account (HRA)
  • Flexible Spending Account (FSA)
  • Company-paid basic life insurance and Additional voluntary life coverage
  • Paid vacation and competitive personal time off
  • 401(k) savings plan with company match
  • Retiree Medical Plans – medical and prescription drug coverage through Novelis sponsored Retiree Health Access
  • Retirement Savings Account
  • Employee assistance programs – available 24/7 to you and your family
  • Wellness and Work Life Support - career development and educational assistance
Disclaimer:

We encourage all potential candidates to follow the protocols below and to be diligent when sharing any personal information:

  • Check the job posting is live and valid via our careers page: Careers - Novelis
  • Verify any communication with us by contacting our talent team at Careers – Novelis

Novelis’ Global Research and Technology Center located in Kennesaw Georgia within the greater Atlanta metropolitan area is a cutting-edge full-service research and technology hub that employs approximately 200 people including world-class engineers metallurgists chemists scientists technologists and technicians. The facility includes state-of-the-art lab equipment and a diverse mix of product pilot lines that bring innovative solutions to customers in the automotive beverage can and specialty markets. Kennesaw provides a diverse and family-friendly place to live with countless museums cultural opportunities and educational institutions. Novelis is committed to the Kennesaw community and supports a number of local charitable organizations including Habitat for Humanity as well as FIRST Robotics aimed at encouraging young people to pursue the Science Technology Engineering and Mathematics (STEM) fields in order to spur the next generation of scientists and innovators.

Novelis recognizes its talented and diverse workforce as a key competitive advantage. Novelis provides equal employment opportunities to all employees and applicants. All terms and conditions of employment at Novelis including recruiting hiring placement promotion termination layoffs recalls transfers leaves of absence compensation and training are without regard to race color religion age sex national origin disability status genetics protected veteran status sexual orientation gender identity or expression or any other characteristic protected by federal provincial or local laws.


We encourage all potential candidates to follow the protocols below and to be diligent when sharing any personal information:
1. Check the job posting is live and valid via our careers page: Careers - Novelis
2. Verify any communication with us by contacting our talent team at Careers - Novelis


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