Location: Remote
The Illinois Department of Public Health is seeking an intern to support its Public Health Informatics team in developing and validating machine learning and artificial intelligence models. This remote internship is ideal for students with a strong technical background in Computer Science, Data Science, or AI, and an interest in public health applications. Interns will have a chance to work on applied projects such as disease forecasting models, chatbot development, and AI troubleshooting—all contributing to real-world public health initiatives. These projects will reflect big groups of policy decision makers, educators, and residents through awareness of some special disease.
Responsibilities
- Assist in the design and development of machine learning models for disease forecasting cases (Measles, Heat-related illness, et. al.).
- Support the creation and validation of AI systems, including chatbots and large language models (Patient discharge data searching system, Epidemiology training system, et. al.).
- Prepare, organize, and validate training datasets.
- Help troubleshoot and refine model performance based on validation results.
- Collaborate with public health informatics staff and contribute to documentation and analysis.
Qualifications
- Current graduate student pursuing Computer Science, Data Science, or a related field.
- Proficient in Python and familiar with machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
- Strong analytical and problem-solving skills.
- Interest in public health and applying technology to societal challenges.
- Experience with natural language processing or chatbot frameworks is a plus.
- With public health background is a plus, but not required.
- Self-motivated and able to work effectively in a remote environment.
- Strong organizational and communication skills.
Duration and Compensation:
This is an unpaid internship with flexible scheduling options to accommodate academic commitments. Academic credit may be available depending on your institution's guidelines. This is a fully remote opportunity for 15 hours a week.
All applications must be submitted by Tuesday, June 3rd by 4:00pm.
