Research Associate, Aerospace Engineering, Daytona Beach Campus

The Opportunity The Department of Aerospace Engineering at Embry‑Riddle Aeronautical University (Daytona Beach Campus) invites applications for a Research Associate position. 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. Job Description This position is ideal for a highly motivated scholar with expertise in machine learning and artificial intelligence, particularly in medical imaging applications. 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) Benefits Generous Time Off: Enjoy 9+ paid holidays, including the day after Thanksgiving and the week between Christmas Eve and New Year’s Day. Tuition Coverage: Get 100% tuition coverage for yourself for one undergraduate and one graduate degree, and discounted rates for your spouse and dependent children up to age 26. Retirement Contributions: ERAU contributes 6% of your base salary to your retirement plan and offers a 4% matching contribution—with no vesting period. Personal Leave: Relax with 12 days of personal leave for non‑exempt employees or 18 days for exempt full‑time employees in your first year. 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) Current Embry‑Riddle employees: Please apply directly through the ERAU Employee Hub Central application within Workday. Equal Employment Opportunity Statement Embry‑Riddle is committed to fostering a workplace where all individuals are valued and respected. We strive to ensure that all faculty, staff, and students are treated fairly and provided equal opportunities for employment, advancement, compensation, training, and other benefits of employment. Embry‑Riddle makes employment decisions—based on individual merit, qualifications, and abilities. We are strongly opposed to discrimination and harassment, and such behavior is prohibited by university policy. Embry‑Riddle does not discriminate on the basis of race, color, national origin, sex, disability, veteran status, predisposing genetic characteristics, age, religion, or pregnancy status, or any other status protected by federal, state, or local law, in its employment, educational programs, admissions policies, financial aid, or other school‑administered programs or activities. For further information, please visit our website. #J-18808-Ljbffr CHEManager International