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Graph Neural Network Internship Jobs (NOW HIRING)

Dayhoff Labs

AI Research Engineer

Cambridge, MA · On-site

$150 - $230/hr

Experience in ML-for-chemistry or ML-for-biology (e.g., neural network potentials, graph neural networks, protein or reaction models) Logistics Compensation is highly competitive. We're also able to ...

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Workday, Inc.

Senior/Principal AI Engineer

Pleasanton, CA · On-site

$139K - $192K/yr

... and/or graph neural network models for real-world use cases * 6+ years of proven experience with cloud computing platforms (e.g. AWS, GCP, etc.) * Proven track record of successfully leading ...

Workday

Senior/Principal AI Engineer

Seattle, WA · On-site

$142K - $196K/yr

... and/or graph neural network models for real-world use cases * 6+ years of proven experience with cloud computing platforms (e.g. AWS, GCP, etc.) * Proven track record of successfully leading ...

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How much do graph neural network internship jobs pay per hour?

As of Aug 20, 2026, the average hourly pay for graph neural network internship in the United States is $17.44, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $19.23 per hour, depending on experience, location, and employer.

What is a graph neural network internship?

A Graph Neural Network (GNN) Internship is a position designed for students or recent graduates to gain hands-on experience working with GNNs, a type of deep learning model that processes data structured as graphs. Interns typically participate in research, model development, and the application of GNNs to various problems such as social network analysis, recommendation systems, or molecular property prediction. The internship provides opportunities to collaborate with experienced researchers, learn cutting-edge techniques, and contribute to real-world projects involving graph-based machine learning.

What types of projects or tasks can I expect to work on during a graph neural network internship?

As a Graph Neural Network (GNN) intern, you will typically be involved in projects such as developing and optimizing GNN models for real-world datasets, implementing new neural network architectures, and conducting experiments to evaluate model performance. You may also assist with data preprocessing, feature engineering, and collaborating with data scientists and machine learning engineers to integrate GNN solutions into larger systems. Regular tasks include reviewing recent research, documenting findings, and presenting your results to the team. This internship offers an excellent opportunity to deepen your understanding of advanced machine learning methods while gaining hands-on experience in a collaborative research-focused environment.

What are the key skills and qualifications needed to thrive as a graph neural network intern, and why are they important?

To thrive as a Graph Neural Network Intern, you need a solid background in machine learning, data science, and programming languages such as Python, often supported by coursework or research experience in deep learning and graph theory. Familiarity with frameworks like PyTorch Geometric, TensorFlow, and libraries such as NetworkX, along with experience using Jupyter Notebooks and Git, is typically expected. Strong analytical thinking, problem-solving skills, and effective communication help interns collaborate with research teams and convey complex ideas clearly. These skills and qualifications are essential for contributing to cutting-edge AI projects and advancing research in graph-based machine learning.
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Graph Neural Network Internship jobs near you
Infographic showing various Graph Neural Network Internship job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 12% Part Time, and 6% Contract. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution, with an average salary of $36,265 per year, or $17.4 per hour.

Graph Neural Network Influenza Modeling Intern

Boston Public Health Commission

Boston, MA • On-site

Internship

Posted 8 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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