University of North Carolina at Chapel Hill
Machine Learning Engineer
Job Description
OUR VISION
Our vision is to be the nation’s leading public school of medicine. We are ranked 2nd in primary care education among all US schools of medicine and 5th among public peers in NIH research funding. Our Allied Health Department is home to five top-ranked divisions, and we are home to 18 top-ranked clinical and basic science departments in NIH research funding.
OUR MISSION
Our mission is to improve the health and well-being of North Carolinians and others whom we serve. We accomplish this by providing leadership and excellence in the interrelated areas of patient care, education, and research.
Patient Care: We will promote health and provide superb clinical care while maintaining our strong tradition of reaching underserved populations and reducing health disparities across North Carolina and beyond.
Education: We will prepare tomorrow’s health care professionals and biomedical researchers by facilitating learning within innovative curricula and team-oriented interprofessional education. We will cultivate outstanding teaching and research faculty, and we will recruit outstanding students and trainees from highly diverse backgrounds to create a socially responsible, highly skilled workforce.
Research: We will develop and support a rich array of outstanding health sciences research programs, centers, and resources. We will provide infrastructure and opportunities for collaboration among disciplines throughout and beyond our University to support outstanding research. We will foster programs in the areas of basic, translational, mechanistic, and population research.
Responsibilities include:
- Develop and implement machine learning models using Python and libraries like PyTorch, possibly using LLMs or ensemble techniques specifically for applications in Radiation Oncology.
- Collaborate with healthcare professionals and researchers to understand clinical needs and translate them into technical requirements.
- Process and analyze medical imaging data, including MRI, CT scans, structured data and free form text, using AI to detect areas of high risk.
- Ensure the accuracy, reliability, and clinical applicability of AI models through rigorous validation and testing.
- Document and communicate model development processes, architecture, and performance metrics to both technical and non-technical stakeholders.
- Master’s degree in computer science, health informatics, artificial intelligence, biomedical engineering, or related field, with a focus on AI/ML preferred.
- Proven experience in programming with proficiency in Python required.
- Knowledge of ML frameworks and libraries, particularly PyTorch or tensorflow or Scikit Learn.
- Understanding of machine learning principles and their application to medical imaging and radiation therapy.
- Ability to work independently on complex projects with interdisciplinary teams.
- Strong problem-solving skills and meticulous attention to detail.
- Excellent communication skills for effective collaboration with healthcare professionals and researchers.
- Experience in handling medical imaging data and familiarity with relevant tools and standards (DICOM, PACS).
- Background in Radiation Oncology, medical physics, or related healthcare field.
- Familiarity with regulatory standards and ethical considerations in healthcare AI applications.
Not Applicable.
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