Multi-Physics Modeling & Scientific Machine Learning Engineer

Job Description Summary

At GE Vernova Advanced Research, we invent and develop cross-cutting transformative technologies to enable a clean and sustainable new era of energy. As a Multi-Physics Modeling & Scientific Machine Learning Engineer within the Aerodynamics & Thermosciences team, you will contribute to the development and application of cutting-edge, high-fidelity, multi-physics modeling techniques and methods to solve complex engineering challenges across GE Vernova's next-generation technology platforms, including and not limited to electrification systems, wind turbines, industrial gas turbines, and nuclear reactors.

You will work in a collaborative, multi-disciplinary environment to revolutionize design and optimization methodologies using physics modeling insights, data-driven physics surrogates of spatio-temporal systems, scientific machine learning at scale and high-fidelity scientific computing on HPC for applications in power generation and electrification technology domains.

• Independently execute tasks using your technical skills for projects at the confluence of physics, computing and machine learning.
• Work as part of a team executing on multi-generation technology programs to enable future design and modeling technology advancements.
• Formulate and develop advanced computational methodologies, implement them according to state-of-the-art software practices
• Execute high fidelity simulations and perform high fidelity computational analyses.
• Use proprietary, opensource and commercial tools as required by the project.
• Participate in systematic validation & verification efforts to advance/demonstrate new technologies.
• Communicate results effectively with stakeholders and document technical findings.

• Doctorate (PhD) in fluid flow physics, computational fluid dynamics (CFD), thermo-sciences, or a closely related discipline.

• Legal authorization to work in the U.S. is required.
• We will not sponsor individuals at the Masters' level for employment visas, now or in the future, for this job opening.
• Must be willing to work out of an office located in Niskayuna, NY

• 2+ years of post-doctoral research experience and/or 3+ years of research experience in an industrial or laboratory setting.
• Research and development experience in advanced computational methods for multiscale physics applications including fluid mechanics, aerodynamics, reacting flows etc.
• Research and development experience in state-of-the-art machine learning algorithms for scientific applications.
• Experience in Python, machine learning libraries (such as PyTorch) and knowledge of deployment at scale on high performance compute clusters.
• Demonstrated proficiency in high-fidelity multiphysics modeling, cutting edge machine learning methods, and high-performance computing
• Outstanding programming skills including expertise with Python, JAX, pyTorch, FORTRAN, C++.
• Knowledge of high-fidelity computational fluid mechanics and thermal analysis tools such as Ansys, COMSOL etc.
• Ability to lead and /or contribute to the development of research proposals to internal business units and external government agencies such as Department of Energy, Department of Defense etc.
• Passion for science and technology and clear evidence of innovation and creativity
• Ability to work effectively in a multidisciplinary team
• Strong interpersonal skills
• Strong analytical skills
• Ability to work under pressure and meet deadlines
• Excellent written and verbal communication skills