Job Description Summary

GE Vernova's Advanced Research Centre (ARC) is the central innovation engine for GE's portfolio of energy businesses, which is unified under one banner called GE Vernova. The research organization is made up of 250+ researchers representing virtually every major scientific and engineering discipline. Collectively, they are driving major research programs and initiatives to decarbonize power, accelerate renewables, and promote electrification and the creation of a 21st century grid fit to power a zero-carbon energy future.

The Digital Research group at ARC is passionate about combining domain models with Operations Research & Machine Learning for industrial applications in the energy sector to prevent failures in industrial equipment, increase their life, and optimize their performance. We are looking for passionate and an enthusiastic individual for solving applied research problems in this industry by building and implementing algorithms for operations optimization and asset performance management. The applicant should have shown research experience in the areas of analytics with a strong mathematical skill and ability to connect physics-based methods with advanced data-based algorithms.

• Develop novel OR/ML algorithms and methodologies applicable to asset performance management and operations optimization problems.
• Analyse large datasets to identify patterns, trends, and insights to deliver algorithms dealing with diagnostics and prognostics of large energy equipment.
• Design and conduct experiments to test the performance and robustness of algorithms for production deployment.
• Document research findings, methodologies, and implementation details for patent disclosures and peer-reviewed publications.
• Collaborate with cross-functional global teams, including engineers, researchers, and product managers, to integrate AI solutions into existing system platforms.
• Keep abreast of the latest advancements in OR/ML through literature and participation in relevant conferences and seminars.

• PhD with 2 - 5 Years Experience or Master's degree with 5 - 7 Years Experience with a focus on operations Research, machine learning, or statistics.
• Specific areas of required expertise are: Mathematical Programming, Discrete Event Simulation, Stochastic Optimization, Machine Learning, Time Series Analysis
• Proficiency in programming languages and packages commonly used in AIML applications such as Python, Tensor Flow, PyTorch, Pandas, Numpy, Gurobi/CPLEX or similar.
• Familiarity with software development best practices, including version control (e.g., Git), and agile methodologies.
• Demonstrated ability to build prototypes and quickly develop proof of concepts to show solution feasibility.

• Strong foundations in the design, analysis, and implementation of algorithms in different computing architectures are desired.
• Experience of working in industrial domains (Power, manufacturing, etc.)
• Enthusiastically follow technology trends, engineering best practice and technologies while enjoying the challenge of solving complex problems
• Self-starter and can work in ambiguous environments
• Excellent problem-solving skills and ability to think critically and creatively
• Strong communication skills and ability to work effectively in a collaborative team environment.