Machine Learning Engineer

at  University of North Carolina at Chapel Hill

POSITION SUMMARY

The Department of Radiation Oncology within the UNC School of Medicine is seeking a dedicated Machine Learning Engineer with a passion for AI in healthcare to serve as a fixed term faculty member at .75 FTE at the rank of Research Instructor. The position will include working with AI fundamentals, Python programming, and ML libraries such as PyTorch. This role involves working with limited supervision to develop and implement effective ML software following current best practices, detailed technical instructions, and contributing to our goals of advancing safety in radiation therapy.

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.

MINIMUM EDUCATION AND EXPERIENCE REQUIREMENTS

Required qualifications include:

• 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.

PREFERRED QUALIFICATIONS, COMPETENCIES, AND EXPERIENCE

Preferred qualifications include:

• 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.

PRIMARY PURPOSE OF ORGANIZATIONAL UNIT

The UNC School of Medicine has a rich tradition of excellence and care. Our mission is to improve the health and wellbeing 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. We strive to promote faculty, staff, and learner development in a diverse, respectful environment where our colleagues demonstrate professionalism, enhance learning, and create personal and professional sustainability. We optimize our partnership with the UNC Health System through close collaboration and commitment to service.

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