1

Computational Materials Science Jobs (NOW HIRING)

MS/PhD in Materials Science, Computational Materials Science, Physics, Chemical Engineering, or related field. * 2-5 years of experience in Computational Materials Science, Materials Informatics ...

Showing results 21-40

Computational Materials Science information

See salary details

$142.5K

$168.8K

$192.5K

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.

Research Scientist I/II, Computational Organic Electronics

Socket.dev

Cambridge, MA • On-site

$176 - $304/hr

Other

Medical, Dental, Vision, Life

Posted 10 days ago


Key responsibilities

  • Apply computational modeling and AI for materials discovery and design of organic electronic materials and devices.

  • Model charge transport, excited‑state behavior, and morphology-property relationships relevant to device performance.

  • Connect simulation outputs to experimental observations and develop workflows that integrate computation and experiment.


Job description

Your Impact at LILA

Your role will involve applying computational methods and AI to accelerate the discovery and design of organic electronics materials. You will use first-principles modeling, atomistic simulations, scientific machine learning, and agentic AI systems to investigate structure-property relationships in organic and hybrid materials relevant to photovoltaics, semiconductors, optoelectronics, or electronic devices.

You will work at the intersection of physics-based simulation, AI/ML, and autonomous scientific workflows. The focus is on using computational insight to identify promising materials, explain structure-property relationships, guide optimization, and help agents reason over simulation and experimental data in scientifically grounded ways.

This is a hands‑on research role for someone who can connect deep organic electronics and computational materials expertise with practical impact for customer‑facing scientific programs. You will collaborate with computational scientists, AI researchers, software engineers, and experimental teams to turn simulations, models, and scientific reasoning into actionable hypotheses and discovery workflows.

What You'll Be Building
  • Apply computational modeling and AI for materials discovery and design of organic semiconductors, photovoltaic materials, molecular and polymeric electronic materials, and organic electronic devices.
  • Model charge transport, excited‑state behavior, morphology-property relationships, and other fundamental mechanisms that influence organic electronic device performance.
  • Connect simulation outputs to experimental observations and develop workflows that close the loop between computation and experiment.
  • Build predictive models from computational and experimental data to guide materials selection and optimization.
  • Analyze simulation and experimental data to generate actionable materials hypotheses.
  • Partner with ML, software, and experimental teams on discovery workflows.
  • Communicate physical insights, model limitations, and recommendations to collaborators.
What You'll Need to Succeed
  • PhD or equivalent experience in Materials Science, Chemistry, Chemical Engineering, Mechanical Engineering, Physics, or a related field.
  • Strong foundation in computational materials science and chemistry, including electronic structure methods and large-scale atomistic simulations.
  • Deep understanding of organic semiconductors, organic electronics, photovoltaics, optoelectronic materials, charge transport, or related device‑relevant materials systems.
  • Experience applying first‑principles, molecular simulations, or general atomistic methods to materials discovery, optimization, or understanding.
  • Ability to connect molecular, morphological, and electronic structure features to device‑relevant properties.
  • Strong programming skills in Python and scientific computing workflows.
Bonus Points For
  • Experience studying organic photovoltaics, organic semiconductors, polymer electronics, molecular electronics, perovskite‑organic interfaces, or related materials systems.
  • Experience applying AI/ML to computational materials science, molecular simulations, or other physics‑based simulations.
  • Strong familiarity with agentic AI systems, autonomous scientific workflows, or simulation‑aware agents.
  • Experience integrating computational predictions with experimental characterization, device measurements, or closed‑loop optimization workflows.
  • Familiarity with charge transport modeling, excited‑state calculations, morphology generation, coarse‑graining, and/or multiscale and multiphysics simulations.
  • Ability to communicate physical insight, uncertainty, and model limitations to cross‑functional collaborators.
Compensation

We offer competitive base compensation with bonus potential and generous early‑stage equity. Your final offer will reflect your background, expertise, and expected impact.

U.S. Benefits. Full‑time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer‑paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.

International Benefits. Full‑time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.

Expected Base Salary Range

$176,000 - $304,000 USD

About LILA

Lila Sciences is building Scientific Superintelligence to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard‑coding expert knowledge into tools, LILA builds systems that can learn for themselves.

LILA combines advanced AI models with proprietary AI Science Factory instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.

Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you’d love to work in, even if you don’t meet every qualification listed above, we encourage you to apply.

We’re All In

Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy.

#J-18808-Ljbffr