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Computational Materials Science Jobs in Washington

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Computational Materials Science information

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$159.2K

$188.7K

$215.1K

How much do computational materials science jobs pay per year?

As of Aug 18, 2026, the average yearly pay for computational materials science in Washington is $188,680.00, according to ZipRecruiter salary data. Most workers in this role earn between $173,800.00 and $203,400.00 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 are the most commonly searched types of Computational Materials Science jobs in Washington?

The most popular types of Computational Materials Science jobs in Washington are:

What job categories do people searching Computational Materials Science jobs in Washington look for?

The top searched job categories for Computational Materials Science jobs in Washington are:

What cities in Washington are hiring for Computational Materials Science jobs?

Cities in Washington with the most Computational Materials Science job openings:

Infographic showing various Computational Materials Science job openings in Washington as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 10% Part Time, 3% Temporary, 6% Contract, and 1% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $188,680 per year, or $90.7 per hour.

Senior Quantum Computational Materials Scientist, US

Phasecraft

Washington, DC

$120K - $175K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 28 days ago


Job description

Phasecraft is the quantum algorithms company. We are building the mathematical foundations for quantum computing applications that solve real-world problems. Founded in 2019 by Toby Cubitt, Ashley Montanaro and John Morton, we are based in London and Bristol in the UK and opened an office in Washington DC in 2024, led by Steve Flammia. In 2025 we completed a $34m Series B funding round co-led by Plural, existing investor Playground Global, and Novo Holdings' Quantum Fund in its first direct quantum software investment.

Phasecraft's unprecedented access to today's best quantum computers - through partnerships with Google, IBM, Quantinuum and QuEra - provides us with unique opportunities to develop foundational IP, inform the development of next-generation quantum hardware, and accelerate commercialization of high-value breakthroughs.

One of the key applications of Phasecraft's quantum algorithms is to modelling materials and molecular systems, where we have demonstrated significant reductions in cost compared with the state-of-the-art.

On the back of these breakthroughs, we are now looking to hire a Senior Quantum Computational Materials Scientist to join our team in Washington DC. In this newly created role, you will play a key role in guiding and coordinating the materials team's research efforts in the US, working closely with the Head of the US office and the materials team lead at Phasecraft. 

The ideal candidate will have extensive experience of research in the theory and application of computational techniques to materials or chemistry simulation, with an interest in applying algorithms for quantum computers to computational materials science. Their work will contribute to Phasecraft's goal of developing quantum algorithms for near-term quantum computers, and may encompass topics such as algorithm design, optimization and implementation, resource analysis, classical and quantum simulation benchmarking. They will have the opportunity to direct and grow a portfolio of research activity across the breadth of Phasecraft's interests.

Job Description

  • Take the role of a senior member of a talented team of scientists undertaking theoretical and applied research on near-term quantum computing algorithms, applications and enabling theoretical technologies.
  • Take initiative within the team to deliver publications, presentations, patent applications and similar resulting from the research.
  • Be a focal point for Phasecraft's interaction with stakeholders on US based collaborations applying quantum computing to materials simulation and discovery.
  • Contribute to new research directions ensuring alignment with the company's overall science strategy.
  • Work within the team to promote an environment of collaboration across a small international team made up of full-time staff and affiliated PhD students.
  • Other activities as required to support the growth and success of Phasecraft.

Requirements

Essential Criteria

  • Expertise in applied and theoretical computational materials science or closely related field.
  • PhD in (ab initio) electronic structure methods, theory and computation, Chemistry, Physics, Materials Science, or a closely related field.
  • Proven track record of working independently on research projects.
  • Deep expertise and an excellent publication track-record in relevant discipline.
  • Excellent written and verbal communication skills and the ability to disseminate research results to technical and non-technical audiences.
  • A deep understanding of the requirements of different funding sources, and the ability to lead efforts and independently write effective grant applications.
  • Flexibility to work across different aspects of quantum algorithms, and to work on other tasks required to support the growth and success of the company.
  • An interest in near-term quantum computing.

  Desirable criteria

  • Experience in materials discovery and use of machine learning methods to enhance workflows.
  • Experience in DFT++ approaches, such as DMFT, DMET, GW etc.
  • Experience in high throughput materials screening applications. 
  • Demonstrable experience in leading multiple complex and collaborative scientific research projects.
  • Experience in developing and growing a team of scientists, promoting an appropriate culture for continuous improvement and knowledge exchange.
  • Enthusiasm for learning and novel research.

Benefits

  • The annual compensation range for this role is $120,000 - $175,000, depending on experience.
  • Health, Vision, Dental, Life Insurance.
  • 401(k) Plan with company matching.
  • Unlimited annual leave.