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Vasp Jobs (NOW HIRING)

SES

Computational Materials Scientist

Woburn, MA · On-site +1

$180K - $200K/yr

Utilize advanced simulation tools (VASP, Quantum Espresso) and data science libraries (TensorFlow, Pandas) to manage and analyze large datasets. Education and/or Experience: * Education: Ph.D. in ...

Mat3ra

Cloud HPC Engineer (Walnut Creek)

Walnut Creek, CA · On-site

$130K - $200K/yr

Work with advanced electronic structure codes (VASP, Quantum ESPRESSO, Gaussian, NWChem, Siesta, or similar) is not required but is a plus * Experience with machine learning Company Benefits Include

Mat3ra

☁ Cloud HPC Engineer ☁

Walnut Creek, CA · On-site

$130K - $200K/yr

... VASP, Quantum ESPRESSO, Gaussian, NWChem, Siesta, or similar) is not required but is a plus * experience with machine learning Benefits Company Benefits Include * Health Care Plan (Medical, Dental ...

Mat3ra

Lead Software Engineer (Node.js)

Walnut Creek, CA · On-site +1

$120K - $180K/yr

... VASP, Quantum ESPRESSO, Gaussian, NWChem, Siesta, or similar) is not required but is a plus * experience with machine learning Benefits Company Benefits Include * Health Care Plan (Medical, Dental ...

Mat3ra

Head of Engineering

Walnut Creek, CA · On-site

$130K - $200K/yr

... VASP, Quantum ESPRESSO, Gaussian, NWChem, Siesta, or similar) is not required but is a plus * experience with machine learning Benefits Company Benefits Include * Health Care Plan (Medical, Dental ...

Mat3ra

Head of Engineering

Walnut Creek, CA · On-site +1

$130K - $200K/yr

... VASP, Quantum ESPRESSO, Gaussian, NWChem, Siesta, or similar) is not required but is a plus * experience with machine learning Benefits Company Benefits Include * Health Care Plan (Medical, Dental ...

Mat3ra

Lead Software Engineer (Node.js)

Walnut Creek, CA · On-site

$120K - $180K/yr

... VASP, Quantum ESPRESSO, Gaussian, NWChem, Siesta, or similar) is not required but is a plus * experience with machine learning Benefits Company Benefits Include * Health Care Plan (Medical, Dental ...

Mat3ra

Lead Frontend Engineer (React.js)

San Francisco, CA · On-site

$120K - $180K/yr

... VASP, Quantum ESPRESSO, Gaussian, NWChem, Siesta, or similar) is not required but is a plus * experience with machine learning Benefits Company Benefits Include * Health Care Plan (Medical, Dental ...

Mat3ra

Lead Frontend Engineer (React.js)

San Francisco, CA · On-site +1

$120K - $180K/yr

... VASP, Quantum ESPRESSO, Gaussian, NWChem, Siesta, or similar) is not required but is a plus * experience with machine learning Benefits Company Benefits Include * Health Care Plan (Medical, Dental ...

Mat3ra

Computational Materials Scientist

Walnut Creek, CA · On-site +1

$90K - $140K/yr

D. from a tier-1 lab) * prior work on advanced electronic structure methods (VASP, Quantum ESPRESSO, Gaussian, NWChem, Siesta, or similar) * prior experience with machine learning Engineering ...

IonQ

Staff Scientist - Materials Science

Bothell, WA · On-site +1

Also valuable: hands-on use of classical packages including QuantumATK, QuantumEspresso or VASP; the ability to design novel fault-tolerant algorithms; a peer-reviewed publication record; client or ...

Mat3ra

Computational Materials Scientist

Walnut Creek, CA · On-site

$90K - $140K/yr

D. from a tier-1 lab) * prior work on advanced electronic structure methods (VASP, Quantum ESPRESSO, Gaussian, NWChem, Siesta, or similar) * prior experience with machine learning Engineering ...

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Vasp information

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How much do vasp jobs pay per hour?

As of Aug 7, 2026, the average hourly pay for vasp in the United States is $26.34, according to ZipRecruiter salary data. Most workers in this role earn between $15.14 and $30.77 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Vasp?

To thrive as a Vasp (Virtual Asset Service Provider), you need a solid understanding of digital asset management, compliance regulations, and cybersecurity protocols, often supported by relevant technical or finance degrees or certifications. Familiarity with blockchain technology, anti-money laundering (AML) systems, and KYC (Know Your Customer) processes is vital in this role. Strong analytical thinking, attention to detail, and communication skills help navigate complex regulations and collaborate with clients and regulatory bodies. These skills ensure secure digital asset transactions and adherence to international financial laws, critical for the reputation and legality of the service provider.

What are some common challenges faced by Vasp professionals in this industry?

Vasp professionals frequently encounter challenges related to evolving regulatory requirements and the rapid advancement of blockchain and digital asset technologies. Staying current with international compliance standards, such as AML and KYC, requires ongoing education and adaptability. In addition, managing cybersecurity risks and building trust with clients and partners can be demanding due to the sensitive nature of digital assets. However, overcoming these obstacles provides valuable experience and positions professionals for growth within the expanding virtual asset sector.

What is a Vasp?

A VASP (Vienna Ab initio Simulation Package) job refers to a computational task performed using VASP, a software for atomic-scale materials modeling. It is commonly used in physics, chemistry, and materials science to perform density functional theory (DFT) calculations. A VASP job typically involves setting up input files, running simulations on high-performance computing systems, and analyzing the results. Researchers use it to study material properties, electronic structures, and atomic interactions.

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Vasp jobs near you
Infographic showing various Vasp job openings in the United States as of August 2026, with employment types broken down into 94% Full Time, and 6% Part Time. Highlights an 70% Physical, and 30% Remote job distribution, with an average salary of $54,791 per year, or $26.3 per hour.

Computational Materials Scientist

SES

Woburn, MA • On-site, Remote

$180K - $200K/yr

Full-time

Medical

Re-posted 6 days ago

Job description

SES AI Corp. (NYSE: SES) is dedicated to accelerating the world's energy transition through groundbreaking material discovery and advanced battery management. We are at the forefront of revolutionizing battery creation, pioneering the integration of cutting-edge machine learning into our research and development. Our AI-enhanced, high-energy-density and high-power-density Li-Metal and Li-ion batteries are unique; they are the first in the world to utilize electrolyte materials discovered by AI. This powerful combination of "AI for science" and material engineering enables batteries that can be used across various applications, including transportation (land and air), energy storage, robotics, and drones.
To learn more about us, please visit: www.ses.ai
What We Offer:
  • A highly competitive salary and robust benefits package, including comprehensive health coverage and an attractive equity/stock options program within our NYSE-listed company.
  • The opportunity to contribute directly to a meaningful scientific project-accelerating the global energy transition-with a clear and broad public impact.
  • Work in a dynamic, collaborative, and innovative environment at the intersection of AI and material science, driving the next generation of battery technology.
  • Significant opportunities for professional growth and career development as you work alongside leading experts in AI, R&D, and engineering.
  • Access to state-of-the-art facilities and proprietary technologies are used to discover and deploy AI-enhanced battery solutions.

What we Need:
The SES AI Prometheus team isseeking an exceptional Computational Materials Scientist to combine physics-based simulation (DFT, MD, quantum modeling) with AI-assisted material prediction to generate high-quality training data and accelerate materials discovery. This role is crucial for advancing our understanding of electrochemical energy materials at the atomic level. As a Computational Materials Scientist, you will be a core data-driven modeler responsible for executing and automating complex simulations.
Essential Duties and Responsibilities:
  • Atomistic Modeling & Simulation
  • Conduct and oversee DFT (Density Functional Theory), MD (Molecular Dynamics), and QM (Quantum Mechanics) simulations of battery components, including electrolytes, coatings, and electrodes.
  • Develop and refine ML-enhanced force fields and surrogate models to accelerate simulation time scales and enable multi-scale simulation efforts.
  • Apply expertise in atomistic simulation and quantum modeling to solve key challenges in electrochemical energy materials (e.g., batteries/fuel cells).
  • AI Data Generation & Prediction
  • Generate high-quality, structured simulation data to serve as training sets for AI property prediction models and material screening modules.
  • Contribute to the development of battery domain LLM features and advanced property-prediction models.
  • Automate complex simulation workflows using strong coding practices to enhance efficiency and scalability.
  • Collaboration & Tooling
  • Collaborate with experimental teams, leveraging a hybrid computational + experimental literacy to validate models and drive design iteration.
  • Utilize advanced simulation tools (VASP, Quantum Espresso) and data science libraries (TensorFlow, Pandas) to manage and analyze large datasets.

Education and/or Experience:
  • Education: Ph.D. in Mechanical Engineering, Materials Science, Chemical Engineering, or a closely related computational/physics field.
  • Core Simulation Expertise: Deep and extensive experience in atomistic simulation and quantum modeling, including proficiency with key QM/DFT tools (VASP, Quantum Espresso) and MD simulations.
  • Domain Focus: Strong background in electrochemical energy materials and extensive computational work focused on batteries/fuel cells.
  • Coding Proficiency: Strong coding skills in Python (along with related libraries like Pandas and TensorFlow) for simulation workflow automation and data analysis.
  • ML Application: Experience in developing or utilizing ML-enhanced force fields and surrogate models for materials prediction., or equivalent practical experience.

Preferred Qualifications:
  • LLM Development: Experience in developing battery domain LLM features or property-prediction models.
  • Hybrid Skillset: Demonstrated experience working in a hybrid computational + experimental environment.
  • Tooling Diversity: Familiarity with additional data analysis tools like R, SQL, MATLAB, and time-series forecasting libraries like Prophet.
  • Target Background: Previous experience at national laboratories, XtalPi, Entalpic, or deep battery modeling groups.

The salary range for this position as required under applicable pay transparency laws.
Salary Range
$180,000-$200,000 USD

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