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Materials Informatics Research Scientist

2 months ago

Dayton, Ohio, United States Riverside Research Full time
Job Title: Materials Informatics Research Scientist

Riverside Research is seeking a highly skilled and innovative Materials Informatics Research Scientist to join our advanced materials team.

Job Summary

The successful candidate will utilize high-performance computing (HPC) and data-driven approaches to accelerate the discovery, design, and optimization of advanced composite materials.

Key Responsibilities
  • Lead the technical direction with government and team, and mentor junior/mid-level staff.
  • Develop and implement high-performance computing models and simulations to study the behavior and performance of advanced composite materials.
  • Utilize data-driven techniques, including machine learning and artificial intelligence to analyze large datasets and extract meaningful insights for material design.
  • Collaborate with material scientists, engineers, and data scientists to integrate computational and experimental data for comprehensive material understanding.
  • Perform multi-scale modeling and simulation to link microstructural features with macroscopic properties.
  • Design and execute computational experiments to predict material properties and guide the development of new composite materials.
  • Analyze simulation and experimental data to validate model and improve their predicative accuracy.
  • Prepare technical reports, presentations, and publications to communicate research findings.
Qualifications
  • Bachelor's degree in materials science, computational science, electrical engineering, or a related field with a focus on high-performance computing and data-driven research with 8 years of experience or 6 years with MS or 3 years with PhD.
  • Must be eligible to obtain a Top Secret security clearance.
  • 5+ years of experience in computational modeling and simulation of composite materials.
  • Proven experience leading a technical project and team.
  • Strong knowledge of high-performance computing platforms and software, such as MPI, OpenMP, CUDA, and related tools.
  • Proficiency in data analytics, machine learning, and artificial intelligence techniques.
  • Experience with multi-scale modeling and integration of different simulation methods.
  • Excellent analytical and problem-solving skills with the ability to interpret complex data.
  • Experience in collaborative research environment, working effectively with cross-functional teams.
Compensation

$130,000 - $220,000 This represents the typical compensation range for this position based on experience, location and other factors.