ZipRecruiter

Log In

1

Graph Neural Network Internship Jobs in Illinois

Cisco

Applied AI Scientist

Chicago, IL · On-site

Our work spans networking, security, observability, and customer experience - designing and ... Large-scale graph representation learning and Graph Neural Networks (GNNs) (e.g., GCN/GAT/GraphSAGE ...

Shure

Applied Research Science Intern

Niles, IL · On-site

$23 - $43/hr

... neural network models and other advanced algorithms * The intern may adapt models for ... Each internship has an hourly rate which varies from $23-$43 per hour based on job function ...

Shure

Applied Research Science Intern

Niles, IL · Hybrid

$23 - $43/hr

... neural network models and other advanced algorithms * The intern may adapt models for ... Each internship has an hourly rate which varies from $23-$43 per hour based on job function ...

New

Shure

Applied Research Science Intern

Niles, IL · Hybrid

$23 - $43/hr

... neural network models and other advanced algorithms * The intern may adapt models for ... Each internship has an hourly rate which varies from $23-$43 per hour based on job function ...

Shure

Applied Research Science Intern

Niles, IL · Hybrid

$23 - $43/hr

... neural network models and other advanced algorithms * The intern may adapt models for ... Each internship has an hourly rate which varies from $23-$43 per hour based on job function ...

State Farm

Data Scientist

Bloomington, IL · Hybrid

Lead/mentor other Data Scientists, interns, and other technical work teams * Make strategic ... Establish and leverage a network of associates with business domain and data expertise * Instill a ...

All JobsGraph Neural Network JobsGraph Neural Network Internship JobsGraph Neural Network Internship Jobs in Illinois

Graph Neural Network Internship information

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.

What are popular job titles related to Graph Neural Network Internship jobs in Illinois?

For Graph Neural Network Internship jobs in Illinois, the most frequently searched job titles are:

What job categories do people searching Graph Neural Network Internship jobs in Illinois look for?

The top searched job categories for Graph Neural Network Internship jobs in Illinois are:

What cities in Illinois are hiring for Graph Neural Network Internship jobs?

Cities in Illinois with the most Graph Neural Network Internship job openings:

Graph Neural Network Internship jobs near you
Infographic showing various Graph Neural Network Internship job openings in Illinois as of August 2026, with employment types broken down into 1% As Needed, 65% Full Time, 29% Part Time, and 5% Contract. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution.

IMSA SIR Neutrino Event Reconstruction in DUNE NDLAr "2×2" with AI/ML

Argonne National Laboratory

Lemont, IL • On-site

Part-time

Posted 4 days ago

Job description

Internship Description
Neutrinos are tiny, nearly massless particles that rarely interact with matter, making them hard to study. The Deep Underground Neutrino Experiment (DUNE) will use large liquid-argon time projection chambers (LArTPCs) to capture the tracks and energy left by particles created when a neutrino interacts. To make the most precise measurements (including whether neutrinos violate CP symmetry), we need accurate, efficient neutrino event reconstruction performed by identifying charged particle tracks from detector data.
In this project, we will use artificial intelligence and machine learning (AI/ML) to help reconstruct and identify particles in the DUNE Near Detector liquid-argon prototype called NDLAr "2×2" (also known as ProtoDUNEND). We'll analyze simulated events and early prototype data to measure how well different AI/ML methods can find and identify particles such as muons, electrons/photons (gammas), protons, and pions.
Education and Experience Requirements
What student will learn and do:
  • Learn the basics of neutrino physics and how LArTPC detectors work.
  • Work in Python and Jupyter notebooks to explore event data and build simple ML models.
  • Use data set with help of AI/ML tools to:
  • Reconstruct particle "objects" from detector hits.
  • Classify particles (e.g., muon vs electron/photon vs proton vs pion).
  • Select a specific interaction channel (e.g., CCQE: chargedcurrent quasielastic) for physics studies.
  • Create visualizations to explain results and uncertainties.
  • Time permitting, compare different models (e.g., a convolutional neural network, CNN, that sees image like views; and a graph neural network, GNN, that operates on point clouds/hits).

Internship Family
Visiting Student High School Research
Internship Category
IMSA Student

Apply