Job Description Summary

As a GE Vernova accelerator, GE Vernova Advanced Research is driving strategy and leading research & development efforts to execute on the business’s mission to help power the energy transition. We forge the collaborations and help invent the technologies required to electrify and decarbonize for a zero-carbon future.

Representing virtually every major scientific and engineering discipline, our researchers are collaborating with GE Vernova’s businesses, the U.S. government, and more than 420 entities at the forefront of technology to execute on 150+ energy focused projects. Collectively, these research programs and initiatives aim to solve near term technical challenges, deliver next generation product advances, and drive long term breakthrough innovation to enable more affordable, reliable, sustainable, and secure energy.

As a global leader in the energy domain, GE Vernova is a purpose-built energy technology company on a mission to electrify and decarbonize the world. Our Artificial Intelligence (AI) team at GE Vernova’s Advanced Research Center is at the heart of this mission, developing and demonstrating innovative AI technologies to transform the future of energy. You can be a part of a highly skilled, dynamic and motivated team of AI Researchers, who are laying the groundwork for GE Vernova to succeed in its mission.

As a Research Scientist specializing in AI for Knowledge Graph and Reasoning, you will design, develop, and apply innovative AI technologies to tackle complex challenges in the energy sector. You will combine techniques in knowledge representation, graph-based machine learning, logical reasoning, generative AI, and foundation models to create explainable and trustworthy AI solutions. Your work will span the entire research spectrum, from fundamental theoretical and empirical investigations to prototyping and solution development. You will investigate and apply techniques to integrate knowledge graphs with Large Language Models (LLMs) to improve explainability, long-term memory, contextual understanding, and reasoning capability for LLM-based solutions as well as to simplify construction and refinement of knowledge graphs to model complex industrial systems, assets, and processes. You will have the opportunity to work on diverse projects with applications in power generation, renewable energy, electric grids, robotics, manufacturing, and internal business processes by collaborating with a broad network of researchers across disciplines and domains. Additionally, you will contribute to cutting-edge research programs with external partners in academia and government, driving the advancement of AI research at GE Vernova and pushing the boundaries of human scientific understanding globally.

Job Description

Roles and Responsibilities

• Research, conceptualize, and develop AI solutions for hard industrial problems by developing and leveraging state-of-the-art capabilities in knowledge representation, graph neural networks (GNNs), generative AI, knowledge graphs (KGs), and advanced reasoning algorithms.

• Collaborate with teams of peer researchers on new and continuing projects 

• Demonstrate value of AI through early prototypes and solutions for real-world problems

• Employ software libraries (e.g., NetworkX, PyTorch Geometric), graph databases (e.g., Neo4j), and industry best practices to build scalable and reusable solutions.

• Create intellectual property by writing invention disclosures and filing patents

• Publish impactful research in top-tier scientific journals and at relevant conferences

• Contribute to writing and securing grant proposals for internal and external funding.

Required Qualifications

• PhD in Computer Science, Electrical/Computer Engineering, Mathematics, Physics, or related fields with a focus on Artificial Intelligence or MS degree in Computer Science, Electrical/Computer Engineering, Mathematics, Physics, or related fields with a minimum of 2 years of work experience with a focus on Artificial Intelligence

• Demonstrated proficiency in programming with Python.

• Familiarity with GenAI packages including models from OpenAI, Google, Meta, etc. and ML frameworks like PyTorch, TensorFlow, etc.

• Expertise in one or more of: (a) integrating LLMs in KG construction from structured and unstructured data, (b) using KG for automated reasoning with generative AI, and (c) creating knowledge graphs that federate and harmonize data from disparate sources.

• Legal authorization to work i