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Day Computational Material Science Jobs (NOW HIRING)

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Day Computational Material Science information

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$56.5K

$83.1K

$98K

How much do day computational material science jobs pay per year?

As of Jul 22, 2026, the average yearly pay for day computational material science in the United States is $83,109.00, according to ZipRecruiter salary data. Most workers in this role earn between $77,500.00 and $93,500.00 per year, depending on experience, location, and employer.

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 strong background in materials science, physics, or chemistry, typically supported by a relevant advanced degree (MSc or PhD). Expertise with simulation software such as VASP, Quantum ESPRESSO, or LAMMPS, as well as proficiency in programming languages like Python or Fortran, is essential. Analytical thinking, problem-solving, and effective communication are standout soft skills for collaborating with interdisciplinary teams and presenting complex data. These skills are crucial for driving innovation, accurately modeling materials, and translating computational results into real-world applications.

What are some common challenges faced by professionals in Day Computational Material Science roles, and how can they be addressed?

Professionals in Day Computational Material Science often encounter challenges such as managing large datasets, integrating experimental and simulation results, and keeping up with rapid advancements in computational methods. Addressing these challenges requires strong collaboration with experimentalists, continual learning to stay updated on new software and algorithms, and effective time management to balance multiple projects. Leveraging open-source tools and participating in interdisciplinary teams can also help overcome technical hurdles and enhance research outcomes.

What is a Computational Material Scientist?

A Computational Material Scientist is a professional who uses computer simulations and theoretical models to study and predict the properties and behaviors of materials. They utilize advanced software and high-performance computing to analyze materials at the atomic or molecular level, helping to design new materials with specific characteristics. Their work supports advancements in fields like electronics, energy, aerospace, and manufacturing by enabling faster and more cost-effective material development compared to traditional experimental methods.

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

AspectDay Computational Material ScienceDay Materials Engineer
Required CredentialsTypically requires a PhD or Master's in materials science, physics, or related fieldsBachelor's or Master's in materials engineering or related disciplines
Work EnvironmentPrimarily research labs, computational environments, and simulation softwareDesign, testing, and manufacturing settings, often in industrial or construction sites
Employer & Industry UsageResearch institutions, universities, R&D departments of tech and manufacturing firmsManufacturing companies, construction firms, product development teams

Day Computational Material Science focuses on computer-based simulations and modeling to understand material properties, while Day Materials Engineer involves practical application, testing, and development of materials in real-world settings. Both roles require strong technical knowledge but differ mainly in their work environment and daily tasks.

What cities are hiring for Day Computational Material Science jobs? Cities with the most Day 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 Day Computational Material Science jobs? States with the most job openings for Day Computational Material Science jobs include:

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 3 days ago


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