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Remote Computational Materials Science Jobs (NOW HIRING)

... materials science, financial modeling, logistics, cybersecurity, and defense. In 2025, the company ... Remote, US Travel: 10% domestic and international travel supporting customer engagements and ...

... Computational Materials Engineering (ICME), seeks an accomplished Enterprise Software and ... Establish credibility within the materials science, advanced manufacturing, and engineering ...

AI Researcher

New York, NY · Remote

$70 - $100/hr

... Science Type: Contract Compensation: $70-$100/hour Location: Remote Commitment: 40 hours/week Role ... Materials Science , or other STEM background. * Demonstrated technical expertise in programming ...

... Science Type: Contract Compensation: $70-$100/hour Location: Remote Commitment: 40 hours/week Role ... Materials Science , or other STEM background. * Demonstrated technical expertise in programming ...

... Science Type: Contract Compensation: $70-$100/hour Location: Remote Commitment: 40 hours/week Role ... Materials Science , or other STEM background. * Demonstrated technical expertise in programming ...

... materials science, financial modeling, logistics, cybersecurity, and defense. In 2025, the company ... Remote, US Travel: 10% domestic and international travel supporting customer engagements and ...

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... data science, molecular and cellular biology, and quantitative physical sciences. The Center ...

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... Computational and Data Sciences (including advanced computing infrastructure), the Materials ...

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Remote Computational Materials Science information

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$56.5K

$83.1K

$98K

How much do remote computational materials science jobs pay per year?

As of Jul 9, 2026, the average yearly pay for remote computational materials science in the United States is $83,109.00, according to ZipRecruiter salary data. Most workers in this role earn between $77,500.00 and $93,500.00 per year, depending on experience, location, and employer.

What is remote computational materials science?

Remote computational materials science involves using computer simulations and modeling techniques to study and design materials, all while working from a remote location rather than in a physical lab. Researchers in this field use software tools to predict the properties and behaviors of materials at the atomic or molecular level, which can accelerate the discovery of new materials for applications in energy, electronics, and manufacturing. Remote computational materials scientists commonly collaborate with teams online, analyze data, and run simulations on high-performance computing systems accessible via the internet.

What are some common challenges faced when working remotely in computational materials science, and how can they be addressed?

Remote computational materials scientists often encounter challenges such as coordinating with interdisciplinary teams across different time zones and ensuring efficient access to high-performance computing resources. Clear communication through regular virtual meetings and collaborative platforms helps maintain project alignment. Additionally, staying organized with version control systems and thorough documentation is essential for seamless teamwork. Being proactive about addressing technical issues, such as software compatibility or data transfer limitations, also ensures productivity.

What is the difference between Remote Computational Materials Science vs Remote Materials Data Analyst?

AspectRemote Computational Materials ScienceRemote Materials Data Analyst
Required CredentialsAdvanced degrees in materials science, physics, or chemistry; experience with computational modelingBachelor's or master's in data science, materials science, or related fields; proficiency in data analysis tools
Work EnvironmentResearch-focused, using simulation software and programmingData processing, visualization, and reporting using analytics platforms
Employer & Industry UsageResearch institutions, R&D departments in manufacturing, tech companiesManufacturers, consulting firms, research labs analyzing material data

Remote Computational Materials Science involves simulating and modeling materials at the atomic or molecular level, requiring programming and scientific expertise. In contrast, Remote Materials Data Analysts focus on analyzing existing material data to inform decisions, emphasizing data skills. Both roles are essential in materials research but differ in their core activities and skill sets.

What are the key skills and qualifications needed to thrive as a Remote Computational Materials Scientist, and why are they important?

To thrive as a Remote Computational Materials Scientist, you need a strong background in materials science, physics, or chemistry, often with a PhD or advanced degree, and expertise in computational modeling. Familiarity with simulation software like VASP, Quantum ESPRESSO, or LAMMPS, as well as proficiency in programming languages such as Python or Fortran, is typically required. Excellent problem-solving skills, self-motivation, and clear written communication are crucial for collaborating remotely and conveying complex results. These competencies enable effective independent research, accurate data analysis, and seamless teamwork in a virtual scientific environment.
More about Remote Computational Materials Science jobs
What cities are hiring for Remote Computational Materials Science jobs? Cities with the most Remote Computational Materials Science job openings:
What are the most commonly searched types of Computational Materials Science jobs? The most popular types of Computational Materials Science jobs are:
What states have the most Remote Computational Materials Science jobs? States with the most job openings for Remote Computational Materials Science jobs include:
Infographic showing various Remote Computational Materials Science job openings in the United States as of July 2026, with employment types broken down into 2% Internship, 70% Full Time, 25% Part Time, 1% Temporary, 1% Contract, and 1% Summer. Highlights an 70% Physical, 1% Hybrid, and 29% Remote job distribution, with an average salary of $83,109 per year, or $40 per hour.
Data Scientist - Materials R&D - Remote-Travel

Data Scientist - Materials R&D - Remote-Travel

Intertape Polymer Group (IPG)

Marysville, MI • On-site, Remote

Full-time

Posted 26 days ago


Intertape Polymer Group rating

6.8

Company rating: 6.8 out of 10

Based on 11 frontline employees who took The Breakroom Quiz

77th of 112 rated packaging manufacturers


Job description

Join the IPG Team!

Are you ready to elevate your career? At IPG, we are more than just a global leader in packaging and protective solutions—we are a community that values safety, people, passion, integrity, performance, and teamwork. From tapes and films to packaging and protective products, as well as engineered coated materials and advanced packaging machinery, we develop innovative solutions that protect the world. Now, we are expanding our global team and looking for talented individuals like you!

This position can be based out of Marysville, MI, or work remotely with some travel as needed.

Title:                                 Senior Data Scientist

Department:                    Research and Development

Immediate Supervisor:   R&D Vice President

Status:                              Exempt Salaried    

 

Position Purpose:            The Senior Data Scientist will support R&D efforts in bio-polymers and sustainable materials and focusing on applying advanced data science, statistical modeling, and machine learning to experimental, process, and materials data to accelerate innovation, improve material performance, and reduce development cycles.

  Principle Accountabilities
  • Partner with polymer scientists, chemists, and engineers to support bio‑polymer research and development using data-driven methods
  • Analyze and model experimental, formulation, and process data to identify structure–property–process relationships
  • Develop predictive models to support:
    • Material performance and property optimization
    • Formulation design and screening
    • Scale‑up and process optimization
  • Design and analyze experiments (DOE) to maximize learning efficiency and reduce development timelines
  • Build and maintain reproducible data workflows for R&D data ingestion, cleaning, and analysis
  • Apply machine learning techniques (e.g., regression, classification, clustering, time-series modeling) to complex scientific datasets
  • Collaborate with data engineering and IT teams to enable scalable data infrastructure for R&D
  • Communicate insights, tradeoffs, and recommendations clearly to technical and non-technical stakeholders
  • Understanding of data visualization best practices
  • Experience working with batch or streaming data processes a plus
  • Contribute to data dictionaries and process flow diagrams for complex data solutions
  • Mentor junior data scientists or technical staff and contribute to data science best practices within R&D
  • Stay current with advances in materials informatics, polymer modeling, and applied AI in scientific research
Essential Skills and Experience 
  • Bachelor’s degree in Data Science, Computer Science, Statistics, Materials Science, Chemical Engineering, or a related field; Master’s or PhD preferred
  • 10+ years of professional experience in data science, applied analytics, or scientific computing; experience working with materials science, polymer science or chemical R&D data, preferred
  • Strong proficiency in Python and/or R for data analysis and modeling
  • Solid experience with SQL and working with structured and semi-structured datasets
  • Strong foundation in statistics, experimental design, and multivariate analysis
  • Demonstrated experience applying machine learning to real-world, noisy scientific or experimental data
  • Ability to work effectively in a cross-functional R&D environment
  • Strong communication skills with the ability to translate complex analyses into actionable insights
  • Familiarity with bio‑polymers, sustainable materials, or polymer processing, preferred
  • Experience with DOE software, laboratory data management systems (LIMS), or scientific databases, preferred
  • Experience deploying models to support R&D decision-making or manufacturing scale-up, preferred
  • Familiarity with cloud platforms (e.g., AWS, Azure) and data science lifecycle tools, preferred
  • Prior experience mentoring or leading technical projects, preferred

Why Choose IPG?

At IPG, you will find more than just a job—you will find a place where your success is our success. We pride ourselves on a culture built around strong relationships, where every team member plays a crucial role in our growth. Whether it is through cross-department collaboration, continuous training, or sustainability-driven initiatives, we create an environment where you can thrive.

Our commitment to sustainability influences everything we do, from designing eco-friendly products to minimizing waste in our production processes. We are dedicated to building a greener future while providing safe, supportive workplaces for our people.

With over 40 years of industry expertise and a proven track record of growth and innovation, IPG offers a stable, secure environment where you can flourish!

We offer competitive pay, extensive benefits that support you and your family, and exciting career development opportunities. Whether you are looking to enhance your skills or advance your career, we offer ongoing training and the support you need to succeed. Think big, dream bigger, and make an impact with IPG.

You belong here. Join us today!


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