Summary

GE Vernova\xe2\x80\x99s Advanced Research business is the central innovation engine for GE\xe2\x80\x99s 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.
We are seeking a highly motivated and talented individual to join our team as an Advanced Research Intern in the field of Control Systems, Optimization, and Estimation. This internship offers an exciting opportunity to work on cutting-edge research projects, collaborate with experienced researchers, and contribute to the advancement of knowledge in control systems theory and applications.

Roles and Responsibilities

• Assist in designing research studies and experiments aimed at addressing key challenges and gaps in control systems theory and practice.
• Develop innovative algorithms and techniques for the optimization and estimation of complex control systems, considering factors such as robustness, stability, and performance.
• Implement control system models and simulations to evaluate the effectiveness and performance of developed algorithms under various scenarios and conditions.
• Analyze experimental data to validate theoretical assumptions, assess algorithm performance, and derive actionable insights for further refinement.
• Conduct comprehensive literature reviews to identify state-of-the-art techniques and methodologies in control systems, optimization, and estimation.
• Collaborate with interdisciplinary teams including engineers, mathematicians, and domain experts to integrate research findings into practical applications and solutions.
• Document research methodologies, results, and findings in technical reports, papers, and presentations for internal and external dissemination.
• Stay abreast of the latest advancements in control systems, optimization, and estimation through continuous learning and engagement with academic and industry literature.

Required Qualifications

• Currently enrolled in a Master\xe2\x80\x99s or Ph.D. program in Electrical Engineering, Mechanical Engineering, Applied Mathematics, or related field, with a focus on control systems, optimization, or estimation.
• Strong theoretical foundation in control theory, optimization theory, and estimation theory.
• Proficiency in mathematical modeling, simulation, and numerical methods for solving complex engineering problems.
• Experience with programming languages and software packages commonly used in research, such as MATLAB, Python, or similar.
• Excellent analytical and problem-solving skills, with the ability to critically evaluate research findings and propose innovative solutions.
• Strong communication and collaboration skills, with the ability to work effectively in a team environment.
• Prior research experience in control systems, optimization, estimation, or related field.

Additional Information

Relocation Assistance Provided: Yes