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Atomistic Simulations Jobs (NOW HIRING)

Microsoft

Principal Quantum Engineer

West Lafayette, IN · On-site

You'll work closely with other experts in atomistic simulations and with fabrication, growth, characterization, and device engineering teams in a fast-paced, interdisciplinary environment. This role ...

SES

Computational Materials Scientist

Woburn, MA · On-site +1

$180K - $200K/yr

Atomistic Modeling & Simulation * Conduct and oversee DFT (Density Functional Theory), MD (Molecular Dynamics), and QM (Quantum Mechanics) simulations of battery components, including electrolytes ...

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Atomistic Simulations information

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$190.5K

How much do atomistic simulations jobs pay per year?

As of Aug 8, 2026, the average yearly pay for atomistic simulations in the United States is $123,399.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,000.00 and $146,500.00 per year, depending on experience, location, and employer.

What are atomistic simulations?

Atomistic simulations are computational methods used to model and study the behavior of materials and molecules at the atomic scale. By simulating the interactions between individual atoms, these techniques help scientists understand material properties, chemical reactions, and biological processes. Common approaches include molecular dynamics (MD) and Monte Carlo simulations, which predict how atoms move and interact over time. Atomistic simulations are widely used in chemistry, physics, materials science, and biology to complement experimental research and design new materials.

What are the key skills and qualifications needed to thrive as an atomistic simulation scientist, and why are they important?

To excel as an Atomistic Simulation Scientist, you need a strong background in physics, chemistry, or materials science, often supported by a relevant advanced degree and experience in computational modeling. Familiarity with simulation software such as LAMMPS, VASP, or GROMACS, as well as programming languages like Python or Fortran, is essential. Strong analytical thinking, problem-solving abilities, and effective communication skills help you interpret results and collaborate with interdisciplinary teams. These competencies are crucial for designing accurate simulations, deriving meaningful insights, and advancing research or product development.

What are some common challenges faced by professionals working in atomistic simulations, and how can they be addressed?

Professionals in atomistic simulations often encounter challenges such as managing large datasets, ensuring the accuracy of computational models, and optimizing simulation performance. Collaborating closely with interdisciplinary teams—including experimentalists, computational scientists, and software engineers—helps overcome these barriers. Staying updated with the latest software tools and high-performance computing resources is also essential for efficient workflow. Regularly validating simulation results against experimental data enhances credibility and reliability in findings.

What is the difference between Atomistic Simulations vs Computational Chemist?

AspectAtomistic SimulationsComputational Chemist
Required CredentialsBachelor's or Master's in Chemistry, Physics, or related fields; knowledge of simulation softwareBachelor's or Master's in Chemistry, Chemical Engineering, or related; strong computational skills
Work EnvironmentResearch labs, academic institutions, industry R&DResearch labs, pharmaceutical companies, academia
Industry UsageMaterial science, nanotechnology, molecular modelingDrug discovery, material design, chemical analysis

Atomistic Simulations involve modeling materials or molecules at the atomic level using computational methods. Computational Chemists apply these techniques to solve chemical problems, often utilizing atomistic simulations as part of their work. While both roles require similar educational backgrounds and work environments, atomistic simulations focus specifically on the simulation techniques, whereas computational chemists may also include data analysis and experimental design.

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What cities are hiring for Atomistic Simulations jobs? Cities with the most Atomistic Simulations job openings:
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Atomistic Simulations jobs near you
Infographic showing various Atomistic Simulations job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 69% Full Time, 27% Part Time, and 3% Contract. Highlights an 69% Physical, 3% Hybrid, and 28% Remote job distribution, with an average salary of $123,399 per year, or $59.3 per hour.

Postdoctoral Fellow - Atomistic Simulations and AI for Materials Design

Johns Hopkins University

Baltimore, MD • On-site

$48K - $66K/yr

Full-time

Re-posted 20 days ago

Johns Hopkins University rating

8.0

Company rating: 8.0 out of 10

Based on 71 frontline employees who took The Breakroom Quiz

184th of 616 rated colleges and universities

Job description

Description
The AtomGPTLab, led by Dr. Kamal Choudhary at Johns Hopkins University, invites applications for a Postdoctoral Fellow position in the fields of atomistic simulations, machine-learned force fields, and artificial intelligence (AI). The successful candidate will lead the development of a computational platform that unifies first-principles methods, classical molecular simulations, and cutting-edge AI techniques including graph neural networks (GNNs) and large language models (LLMs) to accelerate experimental design and discovery of novel materials.
The research spans quantum mechanics, statistical physics, and deep learning, and aims to enable AI-guided predictions of synthesizable and functional materials such as superconductors, catalysts, semiconductors, and energy-relevant compounds. The position is embedded in an interdisciplinary and collaborative environment with active interactions across experimental groups and national laboratories.
Qualifications
Basic Qualifications or Specialized Certifications
  • A PhD in Materials Science, Physics, Chemistry, Chemical Engineering, Computer Science, or a related field.
  • Demonstrated experience in one or more of the following: Density Functional Theory (DFT), machine-learned force fields (MLFF), graph neural networks (GNNs), or large language models (LLMs).

Extensive Knowledge In:
  • First-principles simulations with packages such as VASP, Quantum ESPRESSO, GPAW.
  • Machine-learned interatomic potentials (e.g., ALIGNN-FF).
  • Structure-property prediction using GNNs (e.g., ALIGNN,).
  • LLM fine-tuning and prompt engineering (e.g., HuggingFace, OpenAI, AtomGPT).

Working Knowledge Of:
  • Workflow tools (e.g.,JARVIS-Tools, ASE) and HPC environments.
  • Software development in Python, Git-based version control, and Conda packaging.
  • Data integration and surrogate modeling using experimental and computational datasets.
  • Interdisciplinary collaboration and mentoring of students or junior researchers.

Specific Duties & Responsibilities
  • Conduct high-throughput DFT calculations and manage large-scale materials datasets.
  • Develop GNN architectures for predicting materials properties from atomic graphs.
  • Train and deploy machine-learned force fields for MD simulations and rapid screening.
  • Fine-tune or pre-train LLMs for generation and analysis of materials structures, synthesis protocols, and characterization outputs.
  • Build pipelines for combining experimental and simulated data for inverse design.
  • Provide real-time computational feedback to experimental collaborators for synthesis and characterization.
  • Lead manuscript writing, conference presentations, and contributions to open-source repositories.
  • Mentor undergraduate and graduate students, and participate in grant proposal development.

Additional Opportunities
  • Collaborate as Co-PI on interdisciplinary proposals.
  • Engage with experimental groups, national labs, and industry partners.
  • Participate in the development of open cyberinfrastructure (e.g., AtomGPT.org).
  • Attend international conferences and contribute to global research communities.
  • Access to cutting-edge computing clusters and experimental characterization tools.

Application Instructions
Applicants should submit a curriculum vitae and three recent publications. Review of applications will begin in mid-August 2025.

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About Johns Hopkins University

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Gilman believed that teaching and research go hand in hand—that success in one depends on success in the other—and that a modern university must do both well. He also believed that sharing our knowledge and discoveries would help make the world a better place. In 145 years, we haven’t strayed from that vision. This is still a destination for excellent, ambitious scholars and a world leader in teaching and research. Distinguished professors mentor students in the arts and music, humanities, social and natural sciences, engineering, international studies, education, business, and the health professions. Those same faculty members, along with their colleagues at the university’s Applied Physics Laboratory, have made us the nation’s leader in federal research and development funding every year since 1979. That’s a fitting distinction for America’s first research university, a place that has revolutionized higher education in the U.S. and continues to bring knowledge and discoveries to the world.

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Colleges, universities, and professional schools

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10,000+ Employees

Headquarters location

Baltimore, MD, US

Year founded

1876

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