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Computational Materials Science Jobs (NOW HIRING)

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Computational Materials Science information

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How much do computational materials science jobs pay per year?

As of Sep 5, 2026, the average yearly pay for computational materials science in the United States is $168,844.00, according to ZipRecruiter salary data. Most workers in this role earn between $155,500.00 and $182,000.00 per year, depending on experience, location, and employer.

What is computational materials science?

Computational materials science is a field that uses computer-based simulations and modeling to understand, predict, and design the properties and behaviors of materials. Researchers use mathematical models, algorithms, and high-performance computing to study materials at the atomic, molecular, or macroscopic level. This approach allows scientists to accelerate the discovery of new materials, optimize existing ones, and investigate phenomena that may be difficult or expensive to study experimentally.

What are computational materials science jobs?

Jobs in computational materials science include academic and research positions in university settings. You can also find positions in the manufacturing industry. As a research scientist in computational materials science, your duties are to develop hypotheses and test them using computational modeling software and a variety of investigatory tools, such as Monte Carlo algorithms, density function theory, phase field models, and finite element methods. Your responsibilities include gathering data, testing modeling software, collaborating with other researchers to develop tools that aid them in their research, and analyzing data to write reports, journal articles, or presentations for conferences.

What are the key skills and qualifications needed to thrive as a computational materials scientist, and why are they important?

To thrive as a Computational Materials Scientist, you need a solid background in materials science, physics, or chemistry, often with a graduate degree and experience in scientific computing. Proficiency with simulation software (such as VASP, LAMMPS, or Quantum ESPRESSO), programming languages (like Python, C++, or Fortran), and familiarity with high-performance computing systems is typically required. Critical thinking, problem-solving abilities, and effective collaboration and communication skills set outstanding candidates apart. These competencies are crucial for designing, executing, and interpreting complex simulations and for translating computational insights into real-world materials innovations.

What are some common challenges faced by professionals in computational materials science, and how can they be addressed?

Professionals in Computational Materials Science often encounter challenges such as dealing with large datasets, managing the complexity of multi-scale simulations, and ensuring the accuracy of computational models. Addressing these challenges typically involves staying updated on the latest simulation software, collaborating closely with experimental teams to validate results, and developing strong programming and data analysis skills. Effective communication and interdisciplinary teamwork are also key, as projects often require input from chemists, physicists, and engineers to achieve successful outcomes.

What is the difference between Computational Materials Science vs Materials Engineer?

AspectComputational Materials ScienceMaterials Engineer
Required CredentialsTypically requires a PhD or Master's in materials science, physics, or chemistryBachelor's or Master's in materials engineering or related field
Work EnvironmentResearch labs, universities, or R&D departments focusing on simulations and modelingManufacturing plants, design offices, or product development teams
Industry UsagePrimarily in research, academia, and advanced R&D projectsProduction, quality control, and product development in manufacturing industries
Common Search/ComparisonYesYes

Computational Materials Science focuses on using computer simulations and modeling to understand and predict material behavior, often requiring advanced degrees. Materials Engineers work on designing, testing, and improving materials in practical applications, usually with a bachelor's or master's degree. While both roles are integral to materials development, Computational Materials Science is more research-oriented, whereas Materials Engineering emphasizes application and production.

What cities are hiring for Computational Materials Science jobs?

Cities with the most Computational Materials Science job openings:

What are the most commonly searched types of Computational Materials Science jobs?

The most popular types of Computational Materials Science jobs are:

What states have the most Computational Materials Science jobs?

States with the most job openings for Computational Materials Science jobs include:

Infographic showing various Computational Materials Science job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, 1% Temporary, 2% Contract, and 1% Nights. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $168,844 per year, or $81.2 per hour.

Senior AI Solutions Architect - Materials Science and Chemistry

Nvidia

Santa Clara, CA • On-site

Full-time

Posted 16 days ago


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

6th of 247 rated software companies


Job description

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology-and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing.

An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent. As an NVIDIAN, you'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work.

Come join the team and see how you can make a lasting impact on the world. We are looking for a Senior AI Solutions Architect to support our Materials Science & Chemistry accounts - the chemical and advanced-materials companies, battery and energy-materials makers, materials- and chemistry-software vendors, and research labs adopting accelerated computing and AI across materials discovery, molecular design, and chemical-process engineering. In this role you will be a trusted technical advisor to computational chemists, materials scientists, and R&D engineering teams, embedding NVIDIA accelerated computing, NVIDIA ALCHEMI, physics-informed ML, and Generative AI into atomistic simulation, quantum chemistry, process design, and process-simulation workflows.

You will play a direct role in improving application performance, compressing discovery and formulation cycles, and establishing the technical foundation required for next-generation materials and chemistry systems. What you'll be doing: Support Business Development and Sales teams as part of a small Solutions Architecture team, partnering with Industry Business leads, Account Managers, and Developer Relations managers to drive ecosystem success across Materials Science & Chemistry accounts (chemical and materials companies, battery/energy-materials makers, materials/chemistry ISVs and startups, and research labs). Work directly with computational chemists, materials scientists, and customer R&D and engineering teams in a customer-facing setting.

Help developers GPU-accelerate and scale materials and chemistry workflows - density functional theory (DFT), molecular dynamics (MD), quantum chemistry, machine-learning interatomic potentials (MLIP), high-throughput screening, and generative molecular/materials design - using NVIDIA ALCHEMI and CUDA-X. Apply physics-informed ML and surrogate modeling (e.g., NVIDIA PhysicsNeMo) and accelerate computational fluid dynamics and reaction/transport simulation for chemical-process and formulation workflows. Apply AI/ML and domain-adapted LLMs to materials and chemistry: property prediction, inverse design, materials informatics, and agentic R&D copilots and knowledge retrieval

Analyze materials, chemistry, and process-simulation application architectures and find opportunities for acceleration. Provide feedback and collaborate with engineering, product, and research teams. Deliver trainings, hackathons, and technical demonstrations on NVIDIA solutions and platforms.

What we need to see: BS/MS/PhD in Materials Science, Chemistry, Chemical Engineering, Computational/Physical Chemistry, Condensed-Matter or Applied Physics, Computational Science, or a related technical field (or equivalent experience). 8+ years in computational materials science or chemistry - atomistic simulation (DFT, MD, Monte Carlo), quantum chemistry, materials informatics, or physics-based process/fluid-dynamics simulation - and/or AI/ML applied to these domains. Familiarity with materials/chemistry simulation tools and methods (e.g., VASP, Quantum ESPRESSO, GROMACS, LAMMPS, Gaussian, Schrodinger Suite; DFT, MD, quantum chemistry) and/or machine-learning interatomic potentials (e.g., MACE, NequIP/Allegro) and CFD/reaction-transport for chemical processes

Experience in algorithm programming using languages like Python and C/C++, with familiarity GPU-accelerating compute-intensive workloads. Development experience using major AI frameworks (e.g., PyTorch, TensorFlow) for scientific ML - graph and equivariant neural networks, generative models, or surrogate modeling. Familiarity with accelerated computing platforms, GPU-based distributed systems, and HPC clusters/schedulers (e.g., Slurm)

Familiarity with containers, numerical libraries, modular software design, version control, GitHub. Experience designing, prototyping, and building complex AI/ML-based solutions for customers; able to reason across components such as data pipelines, models, compute, networking, and orchestration. Solid written and oral communication skills and familiarity with collaborative environments.

Team player who can learn, react, and adapt quickly, with an attitude to work in a fast-paced environment. Ways to stand out from the crowd: Experience with NVIDIA ALCHEMI, machine-learning interatomic potentials, or GPU-accelerated DFT/MD and quantum-chemistry workflows. Experience developing physics-ML and surrogate models (NVIDIA PhysicsNeMo, physics-informed neural networks) or GPU-accelerating CFD and reaction/transport solvers for chemical processes.

Background with applying domain-adapted LLMs and agentic AI to chemistry and materials R&D (NeMo, NIM microservices, RAG/knowledge retrieval) and generative molecular/materials design. Experience with Kubernetes, distributed training, and large-scale inference, including DGX Cloud and Run:ai. Background with foundation models for atomistic simulation (e.g., MACE, Orb, UMA) and high-throughput virtual screening, and Omniverse digital twins for chemical-process and fluid-dynamics workflows

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking individuals in the world working for us. If you're creative and autonomous, we want to hear from you.

Widely considered to be one of the technology world's most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/ Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD

You will also be eligible for equity and benefits. Applications for this job will be accepted at least until August 23, 2026. This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.


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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US