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Internship Electrical Engineering Postdoctoral Research information

What is the difference between Internship Electrical Engineering Postdoctoral Research vs Electrical Engineer?

AspectInternship Electrical Engineering Postdoctoral ResearchElectrical Engineer
QualificationsGraduate degree (Ph.D. or equivalent)Bachelor's or Master's degree in Electrical Engineering
Work EnvironmentResearch labs, academic institutions, industry R&DDesign, develop, and test electrical systems in various industries
DurationTypically 6 months to 2 yearsFull-time, ongoing employment
FocusResearch, innovation, academic publishingPractical application, product development, system implementation

In summary, an Internship Electrical Engineering Postdoctoral Research is a temporary research-focused position for recent Ph.D. graduates, emphasizing academic and industry research. An Electrical Engineer is a full-time professional responsible for designing and implementing electrical systems in various industries, requiring a bachelor's or master's degree. Both roles are essential in the electrical engineering field but differ mainly in experience level, focus, and employment type.

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Postdoctoral Research Associate - Generative AI for Fracture Modeling and Digital Twins

Old Dominion University Research Foundation

Norfolk, VA • On-site

$70 - $110/hr

Other

Posted 3 days ago

New

Key responsibilities

  • Define target anatomical representations, assemble datasets, and develop baseline generative models for bone fracture simulation.

  • Introduce fracture-conditioned generation, improve anatomical realism, and incorporate biomechanical and clinical constraints into models.

  • Produce high-resolution anatomical models, validate them for engineering and clinical applications, and prepare publications.

Old Dominion University rating

7.5

Company rating: 7.5 out of 10

Based on 28 frontline employees who took The Breakroom Quiz

314th of 628 rated colleges and universities

Job description

The organization is an equal opportunity and affirmative action employer (AA/EOE/M/F/Disability/VETS/Drug-Free Workplace).

Postdoctoral Research Associate - Generative AI for Fracture Modeling and Digital Twins

Position Number: 26-045

College or Other: BATTEN COLLEGE OF ENGINEERING & TECHNOLOGY

Department: ELECTRICAL & COMPUTER ENGINEERING

FT/PT Status: Full Time

Summary

The Medical Simulation and Computer-Assisted Intervention Laboratory at Old Dominion University invites applications for afull-time Postdoctoral Research Associate to develop next-generationgenerativeAI models for anatomically accurate bone fracture simulation as part of a multidisciplinary translational research program involving Old Dominion University, the University of Virginia, Virginia Tech, and Sonogen Medical. The project is supported through a Virginia Catalyst collaborative award focused on AI-enabled orthopedic technologies and digital twin development.

Project Overview

The successful candidate will lead the development of fracture-aware generative anatomical models capable of producing high-fidelity 3D representations of healthy and fractured skeletal anatomy. These models will support AI algorithm development, digital twins, biomechanical simulation, medical device validation, and future clinical translation.

  • GenerativeAI
  • Medical image analysis
  • Biomechanical simulation
  • Digital twins
  • Orthopedic engineering
  • Medical device innovation
Research Responsibilities

The postdoctoral fellow will execute a one-year research program consisting of four major phases.

  • Months 1–3: Foundation and Baseline Models
    • Define target anatomical representations
    • Assemble and curate CT/MRI/X-ray datasets
    • Build computational infrastructure
    • Develop baseline diffusion and/or GAN-based anatomical generation pipelines
  • Months 4–6: Fracture-Aware Generation
    • Introduce fracture-conditioned generation
    • Improve anatomical realism
    • Incorporate biomechanical and clinical constraints
  • Months 7–9: High-Resolution Modeling and Validation
    • Produce publication-quality anatomical models
    • Integrate finite element and biomechanical plausibility
    • Validate models for engineering and clinical applications
    • Prepare conference and journal publications
  • Months 10–12: Generalization and Software Release
    • Improve robustness and diversity
    • Package reusable software
    • Finalize curated datasets
    • Prepare future NIH, NSF, and DoD proposals

These activities align with the ODU milestones in the Virginia Catalyst project, including foundationgenerativemodels, fracture-aware generation, high-resolution validation, and refinement/generalization.

The successful candidate will have opportunities to

  • Publish in leading AI and biomedical engineering journals
  • Present research at premier international conferences
  • Collaborate with clinicians, orthopedic surgeons, and AI researchers across multiple institutions
  • Participate in development of next-generation AI-enabled medical devices
Appointment
  • Full-time, anticipated to last 12-month r enewable subject to funding availability
  • Start date:Immediately available (preferred)
Job Responsibilities
  • Literature review, including finding relevant open-source software
  • Designing architecture of image analysis system
  • Implementing and training image analysis system
  • Validation of system.
  • Publishing on innovations.
Education and/or training:
  • Ph.D. in Biomedical Engineering, Computer Science, Electrical Engineering, Robotics, Medical Imaging, Applied Mathematics, or related discipline
Level and type ofexperience

Required

  • Strong programming skills in Python
  • Experience with PyTorch or TensorFlow
  • Experience with deep learning and generative AI
Specific knowledge, skills, and abilities:

Preferred

Experience in one or more of:

  • GANs
  • Medical image registration
  • Mesh processing
  • Point clouds
  • Biomechanics
  • Digital twins
  • Scientific computing (CUDA desirable)

Candidates with publications at MICCAI, CVPR, ICCV, ECCV, NeurIPS, ICLR, AAAI, RSNA, or similar venues are especially encouraged to apply.

Other:

Excellent oral and written communication.

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