Research Associate, Aerospace Engineering, Daytona Beach Campus
Embry-Riddle Aeronautical University
Daytona Beach, FL, US
Not specified; benefits: generous time off, 100% t...
Not specified
Ph.d. in machine learning or ai
Expertise in medical imaging applications
Advanced mathematical methods for ml
Embry-Riddle Aeronautical University is seeking a Research Associate for their Department of Aerospace Engineering at the Daytona Beach campus. The role focuses on developing machine learning tools for bone age classification and requires expertise in AI, particularly in medical imaging
Job Summary
The successful candidate will contribute to an interdisciplinary research project focused on developing novel mathematical and machine learning tools for bone age classification using neural networks.
Key responsibilities include conducting cutting-edge research, evaluating deep learning models for medical image analysis, and mitigating high false positive rates in AI-based classification systems.
Embry-Riddle offers generous benefits including 9+ paid holidays, 100% tuition coverage for the employee's degrees, and a 6% retirement contribution with no vesting period.
Matching Summary
Match Score: 85
Embry-Riddle Aeronautical University is seeking a Research Associate for their Department of Aerospace Engineering at the Daytona Beach campus. The role focuses on developing machine learning tools for bone age classification and requires expertise in AI, particularly in medical imaging.
Salary
Not specified; Benefits: Generous time off, 100% tuition coverage, 6% retirement contribution plus 4% match
Skills & Requirements
Must-have
Ph.D. in Machine Learning or AI
Expertise in medical imaging applications
Advanced mathematical methods for ML
Neural network and deep learning experience
Proven track record of scientific publications
Nice-to-have
Experience with healthcare-related AI systems
Familiarity with reducing model false positives
Experience developing user-facing web tools
Key Requirements
Ph.D. in Machine Learning, AI, or Computer Science
Strong background in medical imaging applications
Demonstrated ability in advanced mathematical methods
Proven publication record in peer-reviewed journals