Research Associate, Aerospace Engineering, Daytona Beach Campus

Key Responsibilities

Conduct cutting-edge research on mathematical and computational methods for machine learning applied to bone age classification
Develop and evaluate neural network and deep learning models for medical image analysis
Investigate techniques to mitigate high false positive rates in AI-based classification systems
Contribute to the development of a web-based interface for automated bone age assessment
Publish research findings in peer-reviewed scientific journals and conferences
Collaborate with interdisciplinary research teams
Present work at scientific conferences (travel may be required)

Qualifications

Required Education and Qualifications: Ph.D. (or equivalent doctorate) in Machine Learning, Artificial Intelligence, Computer Science, or a closely related field
Strong background in machine learning and AI, particularly in medical imaging applications
Demonstrated ability in advanced mathematical methods relevant to machine learning
Proven track record of scientific publications or strong potential to publish
Experience with neural networks, deep learning, and related techniques

Preferred Qualifications: Experience with medical image analysis or healthcare-related AI systems
Familiarity with model evaluation and techniques to reduce false positives
Experience developing user-facing tools or web-based applications

Application Process

To submit your application for this opportunity, please visit the Embry-Riddle Career Site and search for requisition number R311165.
Please attach all relevant materials to your application when you apply online.
Complete submissions include: Cover letter, Full CV, Contact information for at least three professional references (please note that references may be contacted as part of the interview/screening process)