GE Vernova AI Research Intern for Time-series Modeling - Summer 2026

Job Description Summary

Join our AI research team to develop the next generation of intelligent systems for the energy sector. As an AI Research Intern for Time-series Modeling, you will tackle the unique challenges of analyzing and forecasting data from critical industrial assets. Your core mission will be to design, build, and validate advanced multi-variate time-series models that go beyond purely data-driven approaches.

The heart of your project will involve innovating on existing or new modeling architectures by integrating fundamental domain knowledge. You will explore cutting-edge techniques to embed physics-based principles, causal relationships, operational constraints, and robust uncertainty quantification directly into your models. This research aims to create more accurate, reliable, and interpretable AI that can enhance the performance and safety of industrial systems, with direct applications in power generation, renewables, and grid management.

Project Outcomes:

• Prototype: A functional proof-of-concept model that demonstrates the successful integration of physics, causality, or uncertainty quantification to improve forecasting or anomaly detection on industrial data.
• Comprehensive Experimental Analysis & Report: A detailed technical report and final presentation summarizing your research methodology, model architecture, and a rigorous comparative analysis against baseline time-series models.
• Validated Codebase: A well-documented and reusable codebase, including data processing pipelines and model implementation, contributed to the team's internal repository.

Potential Contribution to Intellectual Property: Novel research findings and techniques that could form the basis for a patent application or a publication in a leading AI or industrial AI conference.

Primary Skills Developed:

• Industrial Data Analysis: Proficiency in handling the complexities of real-world industrial sensor data, including preprocessing, feature engineering, and interpreting model behavior in the context of physical systems.
• Applied Research & Development Lifecycle: Practical experience of the end-to-end research process in an industrial setting—from problem formulation and experimental design to prototyping, rigorous validation, and results analysis.
• Technical Communication & Documentation: Advanced skills in documenting code, articulating complex technical concepts in reports, and presenting research findings and their implications to a team of experts and business stakeholders.

Basic Qualifications:

• Currently pursuing a M.S./Ph.D. in Computer Science or related fields.
• Legal authorization to work in the U.S. is required.
• Must be willing to work out of an office located in Niskayuna, NY.
• Minimum GPA 4.0 / 5.0 scale or 3.0/4.0 scale.
• Because of the specific categories of data handled by GE Vernova Advanced Research and the structure of our work environment, we are unable to accommodate employment of persons while they are considered nationals of countries subject to comprehensive restrictions under the US Export Administration Regulations (EAR), 15 CFR Section 746 et seq. (currently North Korea, Syria, Iran and Cuba). Please note that citizens of these countries who have either “U.S. person” status under U.S. export control laws or subsequent citizenship or permanent residency from a non-restricted country can be considered.

Desired Qualifications:

• Demonstrated proficiency in programming languages, such as Python
• Solid understanding of AI and machine learning principles
• Hands-on experience with machine learning model development and model training on GPUs
• Ability to work collaboratively within cross-functional teams