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Hourly Machine Learning Intern Jobs in Massachusetts

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Research Scientist Intern, AI Alignment

Boston, MA

$7.6K - $12K/mo

D. degree in Computer Science, Machine Learning, Artificial Intelligence, or relevant technical ... Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual ...

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Hourly Machine Learning Intern information

What is the difference between Hourly Machine Learning Intern vs Hourly Data Science Intern?

AspectHourly Machine Learning InternHourly Data Science Intern
Required CredentialsTypically pursuing or holding a degree in Computer Science, Data Science, or related fields; knowledge of programming and ML frameworksUsually enrolled in or graduated from a program in Data Science, Statistics, or related areas; proficiency in data analysis tools
Work EnvironmentTech companies, startups, research labs focusing on ML model developmentOrganizations applying data analysis to business problems, often in tech, finance, or healthcare sectors
Employer & Industry UsageCommonly used in AI/ML-focused roles within tech industriesWidely used across industries for data-driven decision making

The Hourly Machine Learning Intern focuses on developing and testing machine learning models, requiring programming and ML-specific skills. In contrast, the Hourly Data Science Intern emphasizes analyzing data to extract insights, often involving statistical analysis and data visualization. Both roles are valuable entry points in data-related fields but differ in technical focus and daily tasks.

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Hourly Machine Learning Intern jobs near you

Graph Neural Network Influenza Modeling Intern

Boston Public Health Commission

Boston, MA • On-site

Internship

Posted 4 days ago

Job description

The Graph Neural Network (GNN) Influenza Modeling Intern will support the development and evaluation of machine learning models to improve seasonal influenza forecasting. The intern will analyze historical and current influenza surveillance data, develop and validate forecasting models using Graph Neural Networks, and assess how integrating multiple public health data sources-including emergency department visits, hospitalizations, laboratory testing, immunizations, and wastewater surveillance-affects predictive accuracy. The intern will also build reproducible R and/or Python workflows, support model visualization and deployment, and document processes to ensure long-term sustainability of the forecasting model.
Learning Objectives
  • Gain experience with influenza surveillance systems and public health data sources.
  • Learn and compare traditional forecasting methods with machine learning and Graph Neural Network approaches.
  • Develop and evaluate forecasting models using R and/or Python.
  • Build reproducible analytical workflows and visualizations for public health applications.
  • Document methodologies and support knowledge transfer to BPHC staff.

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