University of North Carolina at Chapel Hill

Machine Learning Engineer

7 June 2024
Apply Now
Deadline date:
£50000 - £100000 / year

Job Description

Posting Information

Department
Radiation Oncology – 413001

Posting Open Date
05/21/2024

Application Deadline

Open Until Filled
Yes

Position Type
Permanent Faculty

Working Title
Machine Learning Engineer

Appointment Type
Fixed Term Faculty

Vacancy ID
FAC0005084

Full-time/Part-time
Part-Time Permanent

Hours per week
30

FTE
0.75

Position Location
North Carolina, US

Hiring Range
Dependent on Experience

Proposed Start Date
07/01/2024

Position Information

Be a Tar Heel!
A global higher education leader in innovative teaching, research and public service, the University of North Carolina at Chapel Hill consistently ranks as one of the nation’s top public universities. Known for its beautiful campus, world-class medical care, commitment to the arts and top athletic programs, Carolina is an ideal place to teach, work and learn.
One of the best college towns and best places to live in the United States, Chapel Hill has diverse social, cultural, recreation and professional opportunities that span the campus and community.
University employees can choose from a wide range of professional training opportunities for career growth, skill development and lifelong learning and enjoy exclusive perks for numerous retail, restaurant and performing arts discounts, savings on local child care centers and special rates on select campus events. UNC-Chapel Hill offers full-time employees a comprehensive benefits package, paid leave, and a variety of health, life and retirement plans and additional programs that support a healthy work/life balance.

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.

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.

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.

Special Physical/Mental Requirements

Campus Security Authority Responsibilities

Not Applicable.


EWJP2