This internship provides hands-on experience applying artificial intelligence and data science in healthcare, specifically within radiation oncology. Interns will work with clinical and non-clinical data to solve complex problems such as image analysis, predictive modeling, and process improvement. The role offers exposure to the full data science lifecycle, including data collection, analysis, algorithm development, and deployment. Interns collaborate with teams to develop analytical solutions, test hypotheses, and apply innovative approaches to improve patient care and healthcare systems.

Responsibilities:

• Apply statistical and computational methods to healthcare data problems
• Assist with data collection, transformation, and data engineering processes
• Perform exploratory data analysis and feature engineering
• Develop, test, and optimize machine learning algorithms
• Support deployment of models into clinical or business environments
• Analyze data related to patient care, outcomes, and operations
• Collaborate with teams to define analytical questions and solutions
• Incorporate feedback from stakeholders to refine models and outputs

Qualifications:

• Currently enrolled in or recently graduated from a program in Computer Science, Data Science, Statistics, Physics, or a related field
• Strong quantitative and analytical skills
• Experience with programming, machine learning, statistics, or algorithms
• Proficiency in Python required
• Familiarity with SQL and linear algebra
• Strong written and verbal communication skills
• Ability to work collaboratively and adapt ideas across industries

Preferred Qualifications:

• Experience with data science tools and structured data analysis
• Experience working with unstructured data such as text, images, or signals
• Familiarity with natural language processing or image analysis
• Experience with additional programming languages such as C, C++, or Java
• Experience with data visualization tools or web-based visualization

Additional Information:

Part-time internship with flexible weekday hours

Work schedule typically between 8:00 AM and 5:00 PM

No weekend work required

Remote work available

Pay Type: Hourly

Compensation: $25.00 per hour

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