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How much do materials informatics scientist jobs pay per year?

As of Jun 24, 2026, the average yearly pay for materials informatics scientist in the United States is $123,973.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,500.00 and $167,000.00 per year, depending on experience, location, and employer.

What does a typical day look like for a Materials Informatics Scientist?

A typical day for a Materials Informatics Scientist often involves analyzing experimental data, developing or refining algorithms to predict materials properties, and collaborating with both experimentalists and computational modelers. You may spend time programming, running simulations, mining large datasets, and presenting your findings to research teams. The role frequently includes interdisciplinary meetings to align goals and strategies, as well as documenting research processes and outcomes. This dynamic work environment offers the opportunity to contribute directly to the development of new materials and to advance the integration of data science within materials research.

What are the key skills and qualifications needed to thrive in the Materials Informatics Scientist position, and why are they important?

To thrive as a Materials Informatics Scientist, you need a solid background in materials science, data analysis, and machine learning, typically supported by an advanced degree in a related field. Experience with programming languages like Python or R, machine learning frameworks, and familiarity with materials databases and analytical software are commonly required. Strong problem-solving abilities, collaboration, and effective communication skills help you connect interdisciplinary teams and convey complex findings. These skills are crucial to effectively integrating computational techniques with experimental research, enabling data-driven materials discovery and innovation.

What is a Materials Informatics Scientist job?

A Materials Informatics Scientist applies data-driven techniques, such as machine learning and artificial intelligence, to analyze and predict the properties and behaviors of materials. They work at the intersection of materials science, data science, and computational modeling to accelerate the discovery and optimization of new materials. Their responsibilities often include developing algorithms, managing large datasets, and collaborating with experimental scientists to validate predictions. This role is essential in industries like electronics, energy storage, and pharmaceuticals, where material performance is critical.

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What are the most commonly searched types of Materials Informatics Scientist jobs? The most popular types of Materials Informatics Scientist jobs are:
What states have the most Materials Informatics Scientist jobs? States with the most job openings for Materials Informatics Scientist jobs include:
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Materials Informatics Scientist jobs near you
Infographic showing various Materials Informatics Scientist job openings in the United States as of June 2026, with employment types broken down into 97% Full Time, 2% Contract, and 1% Nights. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $123,973 per year, or $59.6 per hour.
Materials Informatics Research Scientist

Materials Informatics Research Scientist

Riverside Research

Dayton, OH

$130K - $220K/yr

Full-time

Posted 14 days ago

Job description

Riverside Overview

Riverside Research is an independent National Security Nonprofit dedicated to research and development in the national interest. We provide high-end technical services, research and development, and prototype solutions to some of the country’s most challenging technical problems. All Riverside Research opportunities require U.S. Citizenship.

Position Overview

Riverside Research is seeking a highly skilled and innovative Materials Informatics Research Scientist to join our advanced materials team. The successful candidate will utilize high-performance computing (HPC) and data-driven approaches to accelerate the discovery, design, and optimization of advanced composite materials. Research, develop, test, prototype, demonstrate and transition HPC and data-driven technologies that support the performance prediction of advanced composites materials in aerospace. This role involves working closely with interdisciplinary teams to apply computational methods and data analytics to solve complex material science problems.

Responsibilities

  • Lead the technical direction with government and team, and mentor junior/mid-level staff.
  • Develop and implement high-performance computing models and simulations to study the behavior and performance of advanced composite materials.
  • Utilize data-driven techniques, including machine learning and artificial intelligence to analyze large datasets and extract meaningful insights for material design.
  • Collaborate with material scientists, engineers, and data scientists to integrate computational and experimental data for comprehensive material understanding.
  • Perform multi-scale modeling and simulation to link microstructural features with macroscopic properties.
  • Design and execute computational experiments to predict material properties and guide the development of new composite materials.
  • Analyze simulation and experimental data to validate model and improve their predicative accuracy.
  • Prepare technical reports, presentations, and publications to communicate research findings.

Qualifications

Required Qualifications:

  • Bachelor’s degree in materials science, computational science, electrical engineering, or a related field with a focus on high-performance computing and data-driven research with 8 years of experience or 6 years with MS or 3 years with PhD.
  • Must be eligible to obtain a Top Secret security clearance.
  • 5+ years of experience in computational modeling and simulation of composite materials.
  • Proven experience leading a technical project and team.
  • Strong knowledge of high-performance computing platforms and software, such as MPI, OpenMP. CUDA, and related tools.
  • Proficiency in data analytics, machine learning, and artificial intelligence techniques.
  • Experience with multi-scale modeling and integration of different simulation methods.
  • Excellent analytical and problem-solving skills with the ability to interpret complex data.
  • Experience in collaborative research environment, working effectively with cross-functional teams.

Desired Qualifications:

  • Experience in the aerospace, automotive, or renewable energy industries.
  • Familiarity with materials characterization techniques and their integration with computational models.
  • Experience with grant writing and securing funding for research projects.
  • Capability to develop projects using a mixture of python, MATLAB, C, and data processing languages.

Global Comp

$130,000 - $220,000 This represents the typical compensation range for this position based on experience, location and other factors.

Closing Statement

Riverside Research Institute is a not-for-profit, technology-oriented defense company, where service to our customers and support of our staff is our overall mission. Riverside is an affirmative action-equal opportunity employer and complies with all applicable federal, state, and local laws regarding recruitment and hiring. Riverside offers comprehensive compensation and benefit packages to our employees. Riverside bases its employment decisions solely on technical experience, qualifications and other job-related criteria related to our organizational purpose as a not-for-profit company, and without regard to race, color, religion, age, sex marital status, sexual orientation, national origin, physical or mental disability, veteran’s status or any other status legally protected by applicable federal, state, and local law.

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