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Ai For Science Jobs in Ohio (NOW HIRING)

This role is ideal for an experienced data scientist with strong software engineering and machine learning skills, deep expertise in NLP and Generative AI, and experience developing AI solutions ...

This role is ideal for an experienced data scientist with strong software engineering and machine learning skills, deep expertise in NLP and Generative AI, and experience developing AI solutions ...

Earn incrementally higher pay for each session with the same student, reaching up to $40/hour ... Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ...

ACT Science Tutor

Akron, OH · Remote

$18 - $40/hr

Earn incrementally higher pay for each session with the same student, reaching up to $40/hour ... Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ...

ACT Science Tutor

Cincinnati, OH · Remote

$18 - $40/hr

Earn incrementally higher pay for each session with the same student, reaching up to $40/hour ... Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ...

Earn incrementally higher pay for each session with the same student, reaching up to $40/hour ... Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ...

ACT Science Tutor

Columbus, OH · Remote

$18 - $40/hr

Earn incrementally higher pay for each session with the same student, reaching up to $40/hour ... Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ...

Earn incrementally higher pay for each session with the same student, reaching up to $40/hour ... Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ...

ACT Science Tutor

Cleveland, OH · Remote

$18 - $40/hr

Earn incrementally higher pay for each session with the same student, reaching up to $40/hour ... Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ...

Showing results 41-60

Ai For Science information

What is AI for Science?

AI for Science refers to the application of artificial intelligence and machine learning techniques to accelerate scientific discovery and research. By leveraging large datasets, complex models, and advanced computational methods, AI helps scientists analyze data, identify patterns, simulate experiments, and make predictions across various scientific fields such as biology, chemistry, physics, and climate science. This approach can significantly speed up research, uncover new insights, and solve problems that were previously too complex or time-consuming for traditional methods.

How does collaboration typically work between AI for Science professionals and domain experts in research teams?

AI for Science professionals frequently work closely with experts in fields such as biology, chemistry, or physics to identify scientific problems that can benefit from machine learning techniques. Collaboration usually involves regular meetings to translate complex scientific challenges into data-driven models, sharing domain knowledge, and iteratively refining solutions. Effective communication and a willingness to bridge gaps between computational and scientific perspectives are essential. This interdisciplinary teamwork not only enhances the impact of AI solutions but also fosters ongoing learning and innovation.

What are the key skills and qualifications needed to thrive as an AI for Science specialist, and why are they important?

To thrive as an AI for Science Specialist, you need a strong background in computer science, mathematics, and scientific domains, often supported by advanced degrees (e.g., PhD or MSc) in relevant fields. Proficiency with machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools, and familiarity with high-performance computing environments are typically required. Critical thinking, interdisciplinary collaboration, and effective communication are crucial soft skills for translating scientific problems into AI solutions. These skills are vital for developing innovative models, ensuring research rigor, and enabling impactful scientific discoveries.

What is the difference between Ai For Science vs Data Scientist?

AspectAi For ScienceData Scientist
Required CredentialsDegree in Science, Computer Science, or related fields; knowledge of AI and machine learningDegree in Statistics, Computer Science, or related fields; strong programming skills
Work EnvironmentResearch labs, scientific institutions, tech companies focused on scientific applicationsCorporate, tech firms, finance, healthcare, and other industries analyzing data
Industry UsageApplied to scientific research, simulations, and experimental data analysisUsed for data analysis, predictive modeling, and business insights

Ai For Science focuses on applying AI techniques to scientific research and experiments, often requiring a background in science and specialized knowledge of AI. Data Scientists analyze large datasets across various industries to extract insights and build models. While both roles involve AI and data analysis, Ai For Science is more research-oriented within scientific contexts, whereas Data Scientists work across diverse sectors on data-driven decision making.

What are popular job titles related to Ai For Science jobs in Ohio?

For Ai For Science jobs in Ohio, the most frequently searched job titles are:

What cities in Ohio are hiring for Ai For Science jobs?

Cities in Ohio with the most Ai For Science job openings:

Infographic showing various Ai For Science job openings in Ohio as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 17% Part Time, and 2% Contract. Highlights an 73% Physical, 4% Hybrid, and 23% Remote job distribution.

Development Engineer (AI-Augmented Scientific Modeling)

First Solar

Perrysburg, OH • On-site

Full-time

Re-posted yesterday


First Solar rating

6.6

Company rating: 6.6 out of 10

Based on 77 frontline employees who took The Breakroom Quiz

461st of 545 rated manufacturers


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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