Top 19 computational materials dft Jobs

2026 New College Grad - Computational Chemist / Materials Scientist (Machine Learning – Reactive MLIPs) - Doctorate Degree
Applied Materials —Santa Clara, CA
- $138,000 - $190,000 a year
- Full-time
- Analysis skills
- Doctor of Philosophy
- Travel
Material Scientist - Advanced Technology
Voyager Technologies, Inc. —Denver, CO
- $125,000 - $175,000 a year
- Remote
- Analysis skills
- Doctor of Philosophy
- Senior level
- Dental insurance
- Vision insurance
Quick Apply
Post Doctoral Associate in the Center for Molecular Magnetic Quantum Materials (M2QM)
University of Florida —Gainesville, FL
- $48,000 - $58,000 a year
- University
- Doctor of Philosophy
- Mentoring
Post-Doc Research Associate
University of North Carolina at Chapel Hill —Chapel Hill, NC
- Temporary
- Bachelor of Science
- Mid-level
- University
- Vision insurance
Specialist in Structural Biology*
UC San Francisco Academic —San Francisco, CA
- $55,000 - $194,800 a year
- Online Application
- Master's degree
- University
- Bachelor's degree
Chemical Data Scientist
Schlumberger —Sugar Land, TX
- 6 years
- Office
- Doctor of Philosophy
- Health insurance
- Dental insurance
Computational Materials/Chemistry Engineer
Lam Research —Fremont, CA
- Analysis skills
- Doctor of Philosophy
- Organizational skills
Manager of Research Science
Wolfspeed, Inc. —Durham, NC
- Full-time
- Doctor of Philosophy
- Mentoring
- Manufacturing
- Paid parental leave
- Parental leave
Quick Apply
Postdoctoral Appointee - Building Agentic AI Platform for X-ray Science
Argonne National Laboratory —Lemont, IL
- $72,879 - $121,465 a year
- Full-time
- Background check
- Computer Science
- Analysis skills
Computational Materials and Chemistry, Postdoctoral Research Fellow
Middle Tennessee State University —Murfreesboro, TN
- Temporary
- Doctoral degree
- Computer Science
- University
- Paid holidays
- Health insurance
8d
Modeling and Simulation Manager
Vulcan Elements —Durham, NC
- Management
- 5 years
- Analysis skills
Quick Apply
3d
AI Research Scientist — Agentic AI for Materials Discovery
Meta —Pasadena, CA
- $184,000 - $257,000 a year
- Computer science
- Computer Science
- Bachelor's degree
Sr. Mechanical Design Engineer, Power Electronics
Tesla —Palo Alto, CA
- $109,600 - $195,600 a year
- Full-time
- Analysis skills
- Organizational skills
- In-person
- Commuter assistance
- Health savings account
Automation Engineer, Materials Research Science
Meta —Redmond, WA
- $184,000 - $257,000 a year
- 6 years
- Computer Science
- System design
Artificial Intelligence and Computer Vision for Materials Postdoctoral Research Associate
Los Alamos National Laboratory —Los Alamos, NM
- Email
- Pass drug screening
- Doctor of Philosophy
- In-person
- Disability insurance
- Health insurance
Post-Doctoral Fellow
Worcester Polytechnic Institute —Worcester, MA
- $45,000 - $70,000 a year
- Full-time
- Databases
- University
- Doctor of Philosophy
- Tuition reimbursement
3d
Artificial Intelligence for Materials Postdoctoral Research Associate
Los Alamos National Laboratory —Los Alamos, NM
- Email
- Pass drug screening
- Doctor of Philosophy
- In-person
- Disability insurance
- Health insurance

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2026 New College Grad - Computational Chemist / Materials Scientist (Machine Learning – Reactive MLIPs) - Doctorate Degree

Applied Materials -
Santa Clara, CA

Apply Now

Job Details

Full-time
$138,000 - $190,000 a year

Qualifications

AI models
TensorFlow
Molecular dynamics simulations
PyTorch
High-performance computing clusters
Simulation modeling (chemistry)
AI platforms (beyond public GPTs)
Computational framework
Machine intelligence
Doctor of Philosophy
Simulation tools
Machine learning libraries
Model evaluation
Machine learning frameworks

Full Job Description

Who We Are

Applied Materials is a global leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. We design, build and service cutting-edge equipment that helps our customers manufacture display and semiconductor chips – the brains of devices we use every day. As the foundation of the global electronics industry, Applied enables the exciting technologies that literally connect our world – like AI and IoT. If you want to push the boundaries of materials science and engineering to create next generation technology, join us to deliver material innovation that changes the world.

What We Offer

Salary:

$138,000.00 - $190,000.00

Location:

Santa Clara,CA

You’ll benefit from a supportive work culture that encourages you to learn, develop, and grow your career as you take on challenges and drive innovative solutions for our customers. We empower our team to push the boundaries of what is possible—while learning every day in a supportive leading global company. Visit our Careers website to learn more.

At Applied Materials, we care about the health and wellbeing of our employees. We’re committed to providing programs and support that encourage personal and professional growth and care for you at work, at home, or wherever you may go. Learn more about our benefits .

We are seeking a highly skilled Computational Materials Scientist with deep expertise in machine learning for atomistic modeling, specifically in reactive machine-learned interatomic potentials (MLIPs). This role focuses on developing and deploying ML-driven models capable of accurately capturing bond breaking, bond formation, and complex chemical reactions, enabling predictive simulations at near first-principles accuracy with significantly improved scalability.

The ideal candidate will combine physics-based understanding, advanced machine learning techniques, and strong analytical reasoning to solve challenging problems in materials design and process development.

Key Responsibilities

Develop, train, and deploy reactive MLIPs to model chemical reactions, interfacial processes, and dynamic material behavior.
Build ML models capable of predicting energies, forces, and reaction pathways with near DFT-level accuracy.
Generate and curate high-quality training datasets from DFT and other first-principles methods.
Design and implement active learning workflows to iteratively improve model robustness and coverage of configuration space.
Integrate MLIPs with molecular dynamics (MD) to simulate:
- Reactive processes
- Diffusion and transport
- Oxidation/reduction
- Surface and interface evolution
Apply enhanced sampling techniques (e.g., NEB, metadynamics) in combination with ML models for reaction pathway exploration.
Develop automated simulation pipelines and scalable workflows for high-throughput studies.
Analyze large datasets to extract structure–property and structure–reactivity relationships.
Collaborate cross-functionally with experimental, process, and device teams to guide materials and process optimization.

Required Qualifications

Ph.D. in Materials Science, Physics, Chemistry, or related field.
Demonstrated expertise in reactive machine-learned interatomic potentials (MLIPs) capable of modeling bond breaking and formation.
Hands-on experience with one or more MLIP frameworks:
- MACE, NequIP, GAP, SNAP, DeepMD, or equivalent
Strong background in first-principles methods (DFT) and atomistic simulations (MD).
Proficiency in Python and ML frameworks (PyTorch, TensorFlow).
Experience working in HPC environments and handling large-scale simulations.
Proven ability in dataset generation, labeling strategies, and model validation for ML-based atomistic models.

Core Technical Competencies

Reactive MLIP development and deployment
Machine learning for atomistic simulations
Molecular dynamics and reaction modeling
Materials informatics and data pipelines
High-performance scientific computing

Analytical & Reasoning Requirements

Strong analytical, logical reasoning, and quantitative problem-solving skills.
Demonstrated ability to:
- Diagnose and debug ML model failures and training instabilities
- Critically evaluate model predictions against physical principles
- Ensure physical consistency, transferability, and robustness of simulations
- Identify gaps in training data and design targeted data acquisition strategies
Ability to translate complex physical phenomena into tractable computational models.

Preferred Qualifications

Experience in reactive systems, including:
- Surface chemistry
- Catalysis
- Oxidation/reduction reactions
- Semiconductor or interface materials
Familiarity with uncertainty quantification, Bayesian methods, and active learning.
Experience with:
- ASE, LAMMPS, VASP, or similar tools
- Workflow frameworks (FireWorks, AiiDA, etc.)
Exposure to graph neural networks (GNNs) and equivariant architectures.
Industry experience in materials development or process modeling.

Additional Information

Time Type:

Full time

Employee Type:

New College Grad

Travel:

Yes, 10% of the Time

Relocation Eligible:

Yes

The salary offered to a selected candidate will be based on multiple factors including location, hire grade, job-related knowledge, skills, experience, and with consideration of internal equity of our current team members. In addition to a comprehensive benefits package, candidates may be eligible for other forms of compensation such as participation in a bonus and a stock award program, as applicable.

For all sales roles, the posted salary range is the Target Total Cash (TTC) range for the role, which is the sum of base salary and target bonus amount at 100% goal achievement.

Applied Materials is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, ancestry, religion, creed, sex, sexual orientation, gender identity, age, disability, veteran or military status, or any other basis prohibited by law.

In addition, Applied endeavors to make our careers site accessible to all users. If you would like to contact us regarding accessibility of our website or need assistance completing the application process, please contact us via e-mail at [email protected], or by calling our HR Direct Help Line at 877-612-7547, option 1, and following the prompts to speak to an HR Advisor. This contact is for accommodation requests only and cannot be used to inquire about the status of applications.

Apply Now

Refine Your Search

computational materials dft jobs

2026 New College Grad - Computational Chemist / Materials Scientist (Machine Learning – Reactive MLIPs) - Doctorate Degree

Material Scientist - Advanced Technology

Post Doctoral Associate in the Center for Molecular Magnetic Quantum Materials (M2QM)

Post-Doc Research Associate

Specialist in Structural Biology*

Chemical Data Scientist

Computational Materials/Chemistry Engineer

Manager of Research Science

Postdoctoral Appointee - Building Agentic AI Platform for X-ray Science

Computational Materials and Chemistry, Postdoctoral Research Fellow

Modeling and Simulation Manager

AI Research Scientist — Agentic AI for Materials Discovery

Sr. Mechanical Design Engineer, Power Electronics

Automation Engineer, Materials Research Science

Artificial Intelligence and Computer Vision for Materials Postdoctoral Research Associate

Post-Doctoral Fellow

Artificial Intelligence for Materials Postdoctoral Research Associate

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