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Computational Material Science Jobs (NOW HIRING)

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Computational Material Science information

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$22.5K

$77.4K

$154.5K

How much do computational material science jobs pay per year?

As of Jul 21, 2026, the average yearly pay for computational material science in the United States is $77,385.00, according to ZipRecruiter salary data. Most workers in this role earn between $42,000.00 and $101,000.00 per year, depending on experience, location, and employer.

What is a Computational Material Science job?

A Computational Material Science job involves using computer simulations, modeling techniques, and data analysis to study and predict the properties of materials. Professionals in this field leverage methods like density functional theory (DFT), molecular dynamics, and machine learning to design new materials and optimize existing ones for various applications, including electronics, energy, and manufacturing. They often work in academia, research institutions, or industries such as aerospace, semiconductors, and pharmaceuticals. The role requires expertise in materials science, physics, chemistry, and programming, typically using tools like Python, MATLAB, or specialized simulation software.

What are the key skills and qualifications needed to thrive in the Computational Material Science position, and why are they important?

To thrive in Computational Material Science, you need a strong background in materials science, physics, and computational modeling, usually supported by an advanced degree such as a Master's or Ph.D. Proficiency with simulation software (like VASP, LAMMPS, or Quantum ESPRESSO), high-performance computing environments, and programming languages like Python or C++ is often required. Strong analytical thinking, problem-solving ability, and effective teamwork and communication skills help set professionals apart in this field. These skills are essential for designing, analyzing, and optimizing materials using computational techniques, often as part of collaborative, interdisciplinary research teams.

What are some typical daily tasks for a Computational Material Science professional?

Daily tasks for a Computational Material Science professional often include developing and running computer simulations to investigate material properties, analyzing data from these simulations, and collaborating with experimental scientists to compare computational predictions with laboratory results. You may spend significant time programming, writing reports, and presenting your findings to colleagues or industry partners. You'll typically work within a multidisciplinary team, where clear communication and project coordination are crucial. The balance between independent computational work and collaborative meetings helps ensure innovative solutions to complex material challenges.

More about Computational Material Science jobs
What cities are hiring for Computational Material Science jobs? Cities with the most Computational Material Science job openings:
What are the most commonly searched types of Computational Material Science jobs? The most popular types of Computational Material Science jobs are:
What states have the most Computational Material Science jobs? States with the most job openings for Computational Material Science jobs include:
Infographic showing various Computational Material Science job openings in the United States as of July 2026, with employment types broken down into 2% Internship, 71% Full Time, 25% Part Time, 1% Temporary, and 1% Contract. Highlights an 70% Physical, 1% Hybrid, and 29% Remote job distribution, with an average salary of $77,385 per year, or $37.2 per hour.

PostDoc-Computational Materials Science & Scientific Software Engineering

The businesses of Merck KGaA, Darmstadt, Germany

San Jose, CA โ€ข On-site, Remote

$85K - $128K/yr

Full-time

Medical, Retirement, PTO

Posted 2 days ago

New


Job description

Work Your Magic with us!Start your next chapter and join EMD Electronics.

Ready to explore, break barriers, and discover more? We know you've got big plans - so do we! Our colleagues across the globe love innovating with science and technology to enrich people's lives with our solutions in Healthcare, Life Science, and Electronics. Together, we dream big and are passionate about caring for our rich mix of people, customers, patients, and planet. That's why we are always looking for curious minds that see themselves imagining the unimaginable with us.

Everything we do in EMD Electronics is to help us deliver on our purpose of being the company behind the companies, advancing digital living. We are dedicated to being the trusted supplier of high-tech materials, services and specialty chemicals for the electronics, automotive and cosmetics industries. We foster a global collaborative organization made up of individuals who have the passion to win, obsess about the customer, are relentlessly curious and act with urgency. Together, we push the boundaries of science to make more possible for our customers.


Location: San Jose, California | Remote Flexibility Available

Your Role

You will join an MLIP-powered computational platform for semiconductor materials discovery, working at the intersection of computational chemistry, scientific software engineering, and modern AI. You will design and implement production-grade Python workflows that connect first-principles calculations with machine-learned interatomic potentials to accelerate materials screening and deepen process understanding. You will develop end-to-end simulation pipelines, including slab generation, adsorption energy screening, and molecular dynamics, ensuring code is modular, tested, and well-documented.

You will run and analyze DFT calculations with Quantum ESPRESSO and VASP via ASE, generating high-quality training data for MLIPs and validating results against experimental benchmarks. You will evaluate and deploy MLIP frameworks (such as MACE or UMA), building robust training pipelines, validation protocols, and model-selection workflows. You will implement cheminformatics steps for molecular input preparation, SMILES handling, 3D conformer generation, binding site identification, and NEB-based transition-state searches, linking gas-phase properties to surface workflows. You will operate on HPC infrastructure with SLURM, containerization, and workflow orchestration to ensure reproducibility and scalability.

You will translate domain expert requirements into maintainable, production-grade software and contribute to coding standards, reviews, and CI/CD practices. You will stay curious about AI tooling and be ready to integrate new approaches into scientific workflows. You will collaborate across disciplines, communicating clearly with experimentalists, data scientists, and external partners while delivering tangible software that ships.

Who You Are

Minimum Qualifications:

  • PhD in Computational Chemistry, Quantum Chemistry, Materials Science, Physics, or a closely related field with a strong computational component.

Preferred Qualifications:

  • Solid grounding in quantum chemistry and surface science, including DFT, thermodynamics and kinetics, slab models, and periodic boundary conditions.
  • Hands-on experience with DFT codes and ASE as a simulation interface, plus demonstrated experience with MLIPs and training-data pipelines.
  • Production-grade Python software engineering skills: type hints, docstrings, testing frameworks, linting, modular design, and strong version control with Git and CI/CD practices.
  • Proficiency with HPC environments: job schedulers (e.g., SLURM or PBS), array jobs, containerization (e.g., Apptainer or Docker), and workflow orchestration tools.
  • Basic cheminformatics skills including SMILES handling, three-dimensional conformer generation, binding-site identification, and NEB transition-state searches.
  • Ability to translate research ideas into robust, well-documented code and to work effectively at the research-engineering interface.
  • Strong communication skills and a collaborative mindset, with comfort working across cross-disciplinary teams and with external partners.

Base Pay Range for this position - $85,500-$128,300

The offer range represents the anticipated low and high end of the base pay compensation for this position. The actual compensation offered will be determined by factors such as location, level of experience, education, skills, and other job-related factors. Position may be eligible for sales or performance-based bonuses. Benefits offered by the Company include health insurance, paid time off (PTO), retirement contributions, and other perquisites. For more information click here.


What we offer: We are curious minds that come from a broad range of backgrounds, perspectives, and life experiences. We believe that this variety drives excellence and innovation, strengthening our ability to lead in science and technology. We are committed to creating access and opportunities for all to develop and grow at your own pace. Join us in building a culture of inclusion and belonging that impacts millions and empowers everyone to work their magic and champion human progress!

Apply now and become a part of a team that is dedicated to Sparking Discovery and Elevating Humanity!

Employment Type: Full time