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Computational Modeling Simulation Phd information

What is the difference between Computational Modeling Simulation Phd vs Computational Scientist?

AspectComputational Modeling Simulation PhdComputational Scientist
Required CredentialsPhD in computational sciences, engineering, or related fieldMaster's or PhD in computational or related fields
Work EnvironmentResearch labs, academia, industry R&DResearch institutions, tech companies, industry R&D
Industry UsageDeveloping models, simulations, and algorithms for complex systemsApplying computational methods to solve scientific or engineering problems

Both roles involve advanced computational skills and research experience, but the Computational Modeling Simulation Phd typically focuses on developing and validating models through extensive research, while a Computational Scientist applies these methods to practical problems across various industries.

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Computational Modeling Simulation Phd jobs near you
Infographic showing various Computational Modeling Simulation Phd job openings in Ohio as of August 2026, with employment types broken down into 81% Full Time, 15% Part Time, and 4% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution.

Engineer, Development (AI-Augmented Scientific Modeling)

Perrysburg, OH • On-site

JMJ PHILLIP
See more jobs at JMJ PHILLIPexternal

$130K - $160K/yr

Other

Medical, Dental, Vision, Retirement, PTO

Re-posted 6 days ago

Key responsibilities

  • Develop and implement AI-augmented scientific and engineering models.

  • Design, develop, and validate computational models for engineering and scientific applications.

  • Collect, clean, and analyze large datasets to support predictive modeling.

Job description

We are seeking an Engineer, Development (AI-Augmented Scientific Modeling) to develop and enhance advanced scientific modeling solutions by integrating artificial intelligence, data-driven methodologies, and computational engineering techniques. The ideal candidate is passionate about innovation, enjoys solving complex technical challenges, and has experience applying AI and computational modeling to accelerate research, product development, and engineering decision-making.

Position ResponsibilitiesAI Model Development
  • Develop and implement AI-augmented scientific and engineering models.
  • Integrate machine learning techniques with traditional physics-based modeling approaches.
  • Evaluate and improve model accuracy, scalability, and performance.
Scientific Modeling & Simulation
  • Design, develop, and validate computational models for engineering and scientific applications.
  • Analyze simulation results and recommend design or process improvements.
  • Ensure models accurately represent real-world systems and behaviors.
Data Analysis & Machine Learning
  • Collect, clean, and analyze large datasets to support predictive modeling.
  • Develop algorithms that improve model efficiency and decision-making.
  • Apply statistical and machine learning techniques to solve engineering challenges.
Research & Innovation
  • Stay current with advancements in AI, scientific computing, and emerging technologies.
  • Evaluate new tools and methodologies to improve development capabilities.
  • Contribute to research initiatives and technology roadmaps.
Cross-Functional Collaboration
  • Collaborate with engineering, research, software development, and data science teams.
  • Translate complex technical findings into actionable recommendations.
  • Support product development through technical expertise and analytical insights.
Documentation & Technical Communication
  • Prepare technical documentation, reports, and model validation results.
  • Present findings to internal stakeholders and leadership.
  • Maintain documentation to support knowledge sharing and regulatory compliance where applicable.
Prerequisites
  • Bachelor's, Master's, or Ph.D. in Engineering, Computer Science, Applied Mathematics, Physics, Materials Science, or a related technical field.
  • Experience in scientific computing, computational modeling, simulation, or AI-driven engineering applications.
  • Knowledge of machine learning frameworks and programming languages such as Python, MATLAB, or similar tools.
  • Experience with numerical methods, optimization, and data analysis.
  • Strong analytical, problem‑solving, and communication skills.
  • Ability to work collaboratively in multidisciplinary engineering and research environments.
Certifications (Preferred, but Not Required)
  • AWS Certified Machine Learning – Specialty
  • Microsoft Certified: Azure AI Engineer Associate
  • Google Professional Machine Learning Engineer
  • Certified TensorFlow Developer
  • Data Science or Artificial Intelligence certifications
  • Lean Six Sigma Green Belt
What the Role Offers
  • Salary Range: $130,000 – $160,000 annually.
  • Comprehensive health, dental, and vision insurance.
  • Retirement savings plan with company contributions.
  • Performance-based incentive opportunities.
  • Paid time off and company holidays.
  • Professional development and continuing education support.
  • Access to cutting‑edge AI technologies and research initiatives.
  • Collaborative engineering environment with opportunities for career advancement.
Why Perrysburg?

Perrysburg offers an excellent environment for engineering and technology professionals, with access to a growing innovation ecosystem, advanced manufacturing, and research-driven industries. The area provides opportunities to work on cutting‑edge technologies while enjoying a strong professional community, a high quality of life, and excellent long‑term career growth.

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