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Remote Computational Materials Science Jobs in Ohio

Computational Biology & Cheminformatics Expert Role Type: Contractor Location: Remote micro1 is ... Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance ...

Computational Biology & Cheminformatics Expert Role Type: Contractor Location: Remote micro1 is ... Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance ...

Computational Biology & Cheminformatics Expert Role Type: Contractor Location: Remote micro1 is ... Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance ...

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Remote Computational Materials Science information

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 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.

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 most commonly searched types of Computational Materials Science jobs in Ohio?

The most popular types of Computational Materials Science jobs in Ohio are:

What job categories do people searching Remote Computational Materials Science jobs in Ohio look for?

The top searched job categories for Remote Computational Materials Science jobs in Ohio are:

What cities in Ohio are hiring for Remote Computational Materials Science jobs?

Cities in Ohio with the most Remote Computational Materials Science job openings:

Infographic showing various Remote Computational Materials Science job openings in Ohio as of August 2026, with employment types broken down into 82% Full Time, 13% Part Time, 1% Temporary, 3% Contract, and 1% Nights. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution.

Development Engineer (AI-Augmented Scientific Modeling)

Perrysburg, OH • On-site, Remote


First Solar
Manufacturing • 5 - 10K employees

6.5

Company rating: 6.5 out of 10

Based on 76 frontline employees who took The Breakroom Quiz

474th of 544 rated manufacturers

Recommended by students

Paid breaks

Recommended by parents


Full-time

Re-posted 19 days ago


Job description

First Solar reserves the right to offer you a role most applicable to your experience and skillset. 

Basic Job Functions:

First Solar is seeking a self-driven computational scientist, scientific modeling engineer, applied physicist, or AI-augmented research engineer to help accelerate scientific learning and R&D decision-making. The role combines physical reasoning, computation, data analysis, scientific software, and modern AI-assisted workflows to turn complex observations into practical insight.

This role sits at the intersection of scientific modeling, AI-assisted research workflows, data science, simulation, uncertainty analysis, and engineering decision support. The candidate will develop models, software tools, and analytical workflows that help transform scientific information and experimental results into practical engineering insight.

Education/Experience:

  • Bachelor's degree and 10 years of experience, Master's degree and 8 years of experience, or Ph.D. (strongly preferred) and 5 years of experience in Engineering (Chemical, Electrical, Mechanical, or Computational Science and Engineering) or a related technical field (e.g., Applied Mathematics, Scientific Computing, Physics, Materials Science, Astronomy/Astrophysics, Computational Chemistry, or Computational Biology).

  • Relevant experience must include applying computational, physical, statistical, data-driven, or AI-enabled methods to scientific or engineering challenges.

  • Alternatively, candidates with 2 years of experience as a Development Engineer II at First Solar will be considered.

  • Helpful, but not necessary experience:

    • Experience creating models, software tools, or analytical workflows that influenced experimental decisions, process improvements, engineering decisions, or scientific strategy.

    • Experience building computational pipelines for complex experimental or observational data from microscopy, spectroscopy, scattering measurements, tomography, reliability testing, manufacturing systems, or field-performance monitoring.

    • Experience modeling one or more of the following: transport, diffusion, reaction kinetics, degradation, defect physics, semiconductor behavior, electrochemical systems, materials evolution, or coupled process-structure-property relationships.

    • Familiarity with materials science, photovoltaics, semiconductor devices, thin films, defect chemistry, energy materials, manufacturing process data, or field-performance modeling.

Required Skills/Competencies:

  • Strong written and verbal English communication skills, with the ability to participate effectively in cross-functional technical teams.

  • Experience using modern AI tools and integrating AI-assisted methods into scientific, engineering, or research workflows to accelerate modeling, simulation, software development, literature synthesis, data analysis, or technical decision-making.

  • Demonstrated ability to independently learn new scientific, computational, or analytical methods and apply them to unfamiliar technical problems.

  • Ability to work effectively in ambiguous research environments where the correct model, mechanism, or interpretation is not known in advance.

  • Candidates should demonstrate strength in the following areas:
    • Machine learning, AI-assisted scientific workflows, surrogate modeling, or simulation acceleration.
    • Scientific modeling of physical, chemical, materials, device, or engineering systems.
    • Data analysis, inference, uncertainty assessment, optimization, or model calibration.
    • Scientific software development in Python, Julia, C++, MATLAB, C#, or similar environments.
    • Integration of models and algorithms with experimental, operational, reliability, manufacturing, or field data.
    • Ability to connect scientific understanding with practical engineering decisions.
    • Evidence of scientific curiosity, creativity, intellectual independence, and ability to challenge assumptions constructively.

Essential Responsibilities:

  • Develop and apply machine-learning, generative AI, and physics-informed modeling approaches to explore complex structure-property-performance relationships, identify promising design directions, and accelerate scientific understanding of material systems.

  • Evaluate and apply AI-assisted tools and emerging computational methods that meaningfully improve scientific productivity, model development, data analysis, simulation workflows, or engineering decision quality.

  • Translate physical hypotheses, experimental observations, and engineering questions into scientific models, surrogate models, decision-support tools, and AI-enhanced analytical workflows that help researchers understand complex systems, evaluate competing hypotheses, prioritize opportunities, and guide R&D decisions.

  • Implement scientific models and analysis workflows as reusable computational tools with attention to robustness, computational efficiency, documentation, and reproducibility.

  • Identify knowledge gaps, critical uncertainties, and high-value learning opportunities across research programs, to maximize information gained from experiments and simulations.

  • Use experimental data to support model calibration, parameter estimation, uncertainty assessment, sensitivity analysis, and model validation.

  • Work closely with process development, characterization, reliability, device physics, and other technical teams to improve scientific learning cycles, accelerate problem-solving, and convert research insights into practical engineering actions. 

  • Communicate modeling assumptions, limitations, validation results, uncertainty, and technical conclusions clearly to both specialist and non-specialist audiences.

Reporting Relationships:

  • Report to Fellow, Advanced Research.
  • This position will not have direct reports.

Travel:

  • 0% - 5% (On occasion/as needed for training, etc.)

Estimated Salary Range:

  • $80,700 - $135,000 Annually

Physical Requirements:

All positions in our office require interaction with people and technology while either standing or sitting. To best service our customers, internal and external, all associates must be able to communicate face-to-face and on the phone with or without reasonable accommodation. First Solar is committed to compliance with its obligations under all applicable state and federal laws prohibiting employment discrimination. In keeping with this commitment, it attempts to reasonably accommodate applicants and employees in accordance with the requirements of the disability discrimination laws. It also invites individuals with disabilities to participate in a good faith, interactive process to identify reasonable accommodations that can be made without imposing an undue hardship.

Potential candidates will meet the education and experience requirements provided on the above job description and excel in completing the listed responsibilities for this role. All candidates receiving an offer of employment must successfully complete a background check and any other tests that may be required.      

Equal Opportunity Employer Statement: First Solar is an Equal Opportunity Employer that values and respects the importance of a diverse and inclusive workforce. It is the policy of the company to recruit, hire, train and promote persons in all job titles without regard to race, color, religion, sex, age, national origin, veteran status, disability, sexual orientation, or gender identity. We recognize that diversity and inclusion is a driving force in the success of our company.



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