Non-Student Short-Term Casual

Job Type: Short Term Casual Bargaining Unit: Regular/Temporary: Temporary End Date if Temporary: 06/30/2027 Hours Per Week: 10 Standard Work Schedule: Building: Salary Range: 23pr hr -23pr hr The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training.

The above hiring range represents the University's good faith and reasonable estimate of the range of possible compensation at the time of posting.

Position Summary

The incumbent will support the CIMBID research team by programming and coding image analysis algorithms for the automated visual evaluation of cervical photographs. The student will work closely with Dr. Kontos and the project team to develop, implement, and validate machine learning classifiers applied to the project’s cervical image dataset.

Responsibilities

Develop and implement image analysis algorithms for automated classification of cervical photographs. Apply machine learning and computer vision techniques to medical imaging datasets. Process and analyze image datasets, including quality scoring and feature extraction. Collaborate with the research team to evaluate algorithm performance against clinical outcomes (e.

g., CIN2+, CIN3+ histopathological endpoints). Document code, methods, and results in a clear and reproducible manner. Participate in regular team meetings and provide progress updates. Assist with preparation of research reports and presentations as needed.

Minimum Qualifications

Bachelors Degree. Strong programming skills in Python. Experience with machine learning and/or computer vision libraries (e.g., Py. Torch, Torch. Vision, OpenCV, scikit-learn). Familiarity with data handling and statistical analysis (Num. Py, pandas, Sci. Py, Matplotlib) Preferred Qualifications Experience with medical image analysis or biomedical data.

Familiarity with transformer-based architectures (e.g., Vision Transformers). Background in biomedical engineering, computer science, or a related field. Experience with deep learning model development and validation. Equal Opportunity Employer / Disability / Veteran Columbia University is committed to the hiring of qualified local residents.