This internship position is a time-limited, temporary position with a start date and orientation on January 25th, 2027. The total number of hours that an intern can work during this timeframe is 250 hours.

• Please include your GPA on your resume
• The AI/ML Healthcare Innovation Internship at Cone Health provides a hands-on opportunity to support the AI Center of Excellence in exploring, evaluating, and advancing responsible artificial intelligence and machine learning solutions for healthcare.

Working under the guidance of AI, data, clinical, and technology professionals, the intern will contribute to research, data analysis, model experimentation, documentation, and prototype development. The role is designed for a student who is interested in the intersection of healthcare, engineering, analytics, and applied AI and who wants exposure to real-world clinical and operational workflows.

Essential Job Function:

Assist with research and technical discovery for healthcare AI and machine learning use cases, including summarizing clinical, academic, and industry literature.

• Support exploratory data analysis, data preparation, visualization, and model evaluation using Python, MATLAB, or comparable analytical tools.
• Contribute to supervised prototype development involving machine learning, signal processing, medical imaging, predictive analytics, or workflow automation.
• Help evaluate model performance using defined measures and document findings, assumptions, limitations, and opportunities for improvement.
• Assist with image analysis or segmentation activities using tools such as ImageJ, 3D Slicer, or similar platforms when relevant to an approved project.
• Support analysis of physiologic or time-series data, such as EEG, EMG, heart-rate, or other sensor-based data, when aligned with an approved use case.
• Participate in AI Center of Excellence use-case intake, discovery, and governance activities by preparing research summaries, technical documentation, process maps, and presentation materials.
• Collaborate with clinical, operational, informatics, data, security, compliance, and technology stakeholders to understand problem statements and translate them into well-defined analytical tasks.
• Use approved, appropriately governed data and development environments. Follow all privacy, security, confidentiality, research, and responsible AI requirements.
• Maintain organized project artifacts through version control and team collaboration tools, and communicate progress, risks, and questions to the assigned project lead.
• Prepare a final presentation or demonstration summarizing project objectives, methods, results, lessons learned, and recommended next steps.

Education:

Required:

Must be in process of a college-level degree in a related field and a student in good standing. Junior, senior, or graduate student with a minimum 3.0 GPA in biomedical engineering, computer science, data science, electrical engineering, health informatics, applied mathematics, or a related discipline.