ZipRecruiter

Log In

1

Materials Science Artificial Intelligence Jobs (NOW HIRING)

next page

Showing results 1-20

People also search for

All JobsMaterials Science Artificial Intelligence Jobs

Materials Science Artificial Intelligence information

See salary details

$53K

$124K

$173K

How much do materials science artificial intelligence jobs pay per year?

As of May 31, 2026, the average yearly pay for materials science artificial intelligence 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 are the key skills and qualifications needed to thrive as a Materials Science Artificial Intelligence Specialist, and why are they important?

To thrive as a Materials Science Artificial Intelligence Specialist, you need a strong background in materials science, data analysis, and machine learning, typically supported by a degree in materials science, engineering, computer science, or a related field. Familiarity with programming languages like Python, machine learning frameworks (such as TensorFlow or PyTorch), and materials informatics software is essential. Strong problem-solving skills, interdisciplinary collaboration, and effective communication set top professionals apart in this role. These skills are crucial for developing innovative AI-driven solutions that accelerate materials discovery and optimization.

How do professionals in Materials Science Artificial Intelligence typically collaborate with experimental scientists during research projects?

In Materials Science Artificial Intelligence roles, collaboration with experimental scientists is frequent and essential. AI specialists work closely with lab-based researchers to interpret data, validate predictive models, and design experiments that can efficiently test AI-generated hypotheses. Open communication and cross-disciplinary meetings are common, as AI experts rely on experimental feedback to refine algorithms, while experimentalists use AI insights to streamline their research. This partnership accelerates materials discovery and ensures that computational models remain grounded in real-world results.

What is Materials Science Artificial Intelligence?

Materials Science Artificial Intelligence is the application of AI and machine learning techniques to materials science research and development. It involves using algorithms to analyze large datasets, predict material properties, design new materials, and optimize manufacturing processes. This interdisciplinary field accelerates material discovery and helps scientists make data-driven decisions, ultimately leading to innovative materials for various industries. Professionals in this area often have expertise in both materials science and computer science.

What is the difference between Materials Science Artificial Intelligence vs Materials Engineering?

AspectMaterials Science Artificial IntelligenceMaterials Engineering
Required CredentialsTypically requires a degree in computer science, data science, or materials science with AI specializationRequires a degree in materials engineering, metallurgical engineering, or related fields
Work EnvironmentResearch labs, tech companies, or academia focusing on AI applications in materialsManufacturing plants, R&D labs, or industrial settings focused on material development and processing
Industry UsageUsed for developing predictive models, data analysis, and machine learning applications in materialsInvolved in designing, testing, and producing materials for various industries

Materials Science Artificial Intelligence focuses on applying AI and data science techniques to materials research, while Materials Engineering emphasizes the practical development and manufacturing of materials. Both roles often collaborate but differ in their core skills and work environments.

Infographic showing various Materials Science Artificial Intelligence job openings in the United States as of May 2026, with employment types broken down into 88% Full Time, 11% Part Time, and 1% Contract. Highlights an 85% Physical, 6% Hybrid, and 9% Remote job distribution, with an average salary of $123,973 per year, or $59.6 per hour.
ChemBE Systems/Data Science/Artificial Intelligence Professor - all ranks

ChemBE Systems/Data Science/Artificial Intelligence Professor - all ranks

Johns Hopkins University

Baltimore, MD • On-site

$150K - $200K/yr

Full-time

Posted 16 days ago

Johns Hopkins Medicine rating

7.5

Company rating: 7.5 out of 10

Based on 200 frontline employees who took The Breakroom Quiz

217th of 864 rated healthcare providers

Job description

Description
Faculty position in Chemical and Biomolecular Engineering
Johns Hopkins
The Johns Hopkins University's Department of Chemical and Biomolecular Engineering seeks applicants for tenure-track/tenured faculty positions. Candidates with research and teaching interests in Systems Theory (Design -from plant level to molecular- and/or Control) with a strong component in Data Science/Artificial Intelligence (DSAI) relevant to chemical and biomolecular engineering will be considered.
Candidates in these areas will contribute to the Department of Chemical and Biomolecular Engineering and Johns Hopkins University community and mission to educate tomorrow's leaders in ChemBE and pioneer technological advancements to address critical global challenges in energy, materials design, and precision medicine, to build a stronger, cleaner, and healthier future.
Candidates in the Systems/Data Science/Artificial Intelligence area will perform original research at the interface between chemical engineering modeling/scientific computation and modern Data Science and Machine Learning. Possible efforts include but are not limited to modern design and optimization (e.g. in the role of AI in the transition from automated to autonomous process operations). Creative uses of DSAI in materials/chemicals/process discovery/design, or towards novel computational approaches to atomistic simulations or biological systems modeling are of direct interest.
The Department of Chemical and Biomolecular Engineering is highly collaborative with an established track record of national leadership and developing new disciplines within chemical and biomolecular engineering. The Department has large, vibrant educational programs at the undergraduate, master's, and Ph.D. levels as well as post-doctoral level.
This past year, Johns Hopkins announced a major new investment in Data Science and the exploration of Artificial Intelligence that will be included in a new data science and translation institute, a new state-of-the-art facility and recruitment of 110 new faculty over the next five years. The institute will bring together world-class experts in artificial intelligence, machine learning, applied mathematics, computer engineering, and computer science to fuel data-driven discovery in support of research activities across the institution including within the Chemical and Biomolecular Engineering department.
In addition to its role in this initiative, the department is a leader in other major research centers and institutes at Johns Hopkins, including the Ralph O'Connor Sustainable Energy Institute (ROSEI), the Institute for Nanobiotechnology (INBT), the Advanced Mammalian Biomanufacturing Innovation Center (AMBIC), International Biomanufacturing Network (IBIoNe) MINDS (Mathematical Institute for Data Science), the Maryland Area Research Computing Center (MARCC), the Hopkins Extreme Materials Institute (HEMI). Faculty also collaborate frequently with scholars in the Johns Hopkins School of Medicine, Applied Physics Laboratory, Bloomberg School of Public Health, and the Krieger School of Arts and Sciences.
Applicants should have a Ph.D. in chemical and biomolecular engineering or a related field, a track record of outstanding research, and a commitment to excellence in education and student mentoring.
The expected base pay range for this position at a rank of Assistant Professor is $150,000-$200,000.
The referenced salary range reflects base pay, which is based on faculty rank and years in rank. This salary range does not include all components of the WSE/ChemBE faculty compensation program or pay from participation in WSE/ChemBE incentive compensation programs. Therefore, the actual compensation paid to the selected candidate may vary from the salary range stated herein. For more information, please contact the hiring department.
Priority given to applications received before 12/31/2025.
Application Instructions
Interested candidates should submit a cover letter, CV, references, and research and teaching statements.

What Johns Hopkins Medicine employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply