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Locum Graduate Materials Science Jobs (NOW HIRING)

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Locum Graduate Materials Science information

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$11K

$284.8K

$400K

How much do locum graduate materials science jobs pay per year?

As of Aug 21, 2026, the average yearly pay for locum graduate materials science in the United States is $284,795.00, according to ZipRecruiter salary data. Most workers in this role earn between $224,500.00 and $328,500.00 per year, depending on experience, location, and employer.

What cities are hiring for Locum Graduate Materials Science jobs?

Cities with the most Locum Graduate Materials Science job openings:

What are the most commonly searched types of Graduate Materials Science jobs?

The most popular types of Graduate Materials Science jobs are:

What states have the most Locum Graduate Materials Science jobs?

States with the most job openings for Locum Graduate Materials Science jobs include:

Infographic showing various Locum Graduate Materials Science job openings in the United States as of June 2026, with employment types broken down into 7% As Needed, 17% Full Time, 69% Part Time, and 7% Contract. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution, with an average salary of $284,795 per year, or $136.9 per hour.

Materials Science Ai Engineer

Cardinal Integrated Technologies Inc

Santa Clara, CA • On-site

Full-time

Re-posted 28 days ago


Job description

Job Summary:
Cardinal Integrated Technologies Inc is seeking a Materials Science AI Engineer to join their team in developing and supporting materials discovery and design. The ideal candidate will focus on building AI-based solutions and collaborating with scientists and engineers to integrate analytics into core R&D workflows.
Responsibilities:
• Design, develop and deploy multi-modal AI, ML, and hybrid physical-based models to solve ground-breaking material physics and design problems.
• Aggregate, process, transform and quality-control experimental and simulation data for modeling and analysis.
• Design, develop, and maintain data workflows to support materials informatics initiatives. Optimize data pipelines and model execution on parallel cloud systems (e.g., Azure, GCP, AWS).
• Collaborate with materials scientists, chemists, and software engineers to integrate analytics and predictive modeling into core R&D workflows.
• Document code, workflows, and best practices to support reproducible research.
• Apply AI and data analytics to optimize material synthesis and processing parameters in real-time, minimizing defects, improving consistency.
Qualifications:
Required:
• Strong proficiency in programming languages like Python and C++.
• Experience with machine learning and deep learning frameworks (e.g., PyTorch, TensorFlow).
• Experience with data cleansing, preprocessing, and feature engineering
• Graduate or undergraduate degree in Computer Science, Engineering, Applied Mathematics, or a related technical field.
• 2-4 years of work experience (depending on educational degree) in data science, AI, machine learning, or data engineering roles.
• A strong foundation in the principles of materials science is essential to understand the underlying science and set up meaningful problems for AI.
• Expert in Python and data science libraries (e.g., pandas, NumPy, scikit-learn, TensorFlow or PyTorch).
• Expertise in use of cloud-based compute environments and tools for parallel or distributed computing.
• Strong problem-solving and communication skills.
Preferred:
• Design, develop and deploy multi-modal AI, ML, and hybrid physical-based models to solve ground-breaking material physics and design problems
Company:
We are a company of IT professionals who passionately believe that good quality products & services are delivered by great resources. Founded in 2013, the company is headquartered in Monmouth Junction, USA, with a team of 201-500 employees. The company is currently Growth Stage.