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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Multi-Physics Modeling & Scientific Machine Learning Engineer - **Company:** GE Vernova - **Location:** Niskayuna, NY, United States - **Experience:** Experienced - **Salary:** $89,300.0 - **Contract:** Permanent contract - **Skills:** Confluence, C++ (Programming Language), Computational Fluid Dynamics, Computer Simulation, Computer Programming, Comsol Multiphysics, Fortran (Programming Language), Python (Programming Language), Machine Learning, Open Source Technology, Scientific Computating, High Performance Computing, Pytorch, Data Analytics, Multiaccess Edge Computing, Ansys, Software Library - **Published:** September 3, 2026 - **Apply:** https://www.themuse.com/jobs/gevernova/multiphysics-modeling-and-scientific-machine-learning-c2a1ce ## About the Role * Doctorate (PhD) in fluid flow physics, computational fluid dynamics (CFD), thermo-sciences, or a closely related discipline. Eligibility: * 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 ## Description 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. ## Related Videos - [Data Science, ML & AI in the Oil and Gas Industry at NDT Global - Dr. Katja Träumner](https://www.wearedevelopers.com/videos/1308-data-science-ml-ai-in-the-oil-and-gas-industry-at-ndt-global-dr-katja-traumner) - [Cloud Vendor Lock-In - Is it just a new version of the Database Abstraction Layers?](https://www.wearedevelopers.com/videos/1185-cloud-vendor-lock-in-is-it-just-a-new-version-of-the-database-abstraction-layers) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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