Computational Methods Post Doctorate

GE Vernova

Niskayuna, United States

Full Time

Posted September 18, 2026

$89k - $89k

Power Generation

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Listing evidence and provenance

Source: workday View original listing
Freshness: Open in the current public read path; this is not an employer guarantee.Last observed September 30, 2026
Classification: Modern power-system classification not yet published for this listing.Legacy source industry field: Power Generation
Pay provenance: Employer-provided pay

Job Description

At GE Vernova Advanced Research, we invent and develop cross-cutting transformative technologies to enable a clean and sustainable new era of energy.

Key Responsibilities

Independently conduct research and develop advanced computational models and simulation tools for complex physical systems, including multi-physics, multi-phase, and multiscale phenomena.
Apply and extend high-fidelity simulation methods such as computational fluid dynamics (single and multi-phase flows), heat transfer, reactive flows, and combustion using both commercial and proprietary software.
Develop and implement novel numerical algorithms, including machine learning enhanced simulations and reduced-order modeling techniques.
Participate in verification and validation activities to ensure model accuracy and robustness against experimental data.
Collaborate closely with experimentalists and domain experts to ensure high-quality data integration and model calibration.
Contribute to the advancement of GE Vernova’s digital engineering capabilities, including digital twins and model-based systems engineering.
Innovate in the field of computational methods by exploring emerging technologies such as GPU-accelerated computing, uncertainty quantification, and real-time simulation.
Effectively communicate technical results through detailed reports, peer-reviewed publications, and presentations to internal teams and external stakeholders.
Support the development of proposals for GE Vernova businesses and government funding agencies.
Connect GE Vernova to the latest advancements in computational science, ensuring alignment with global trends and academic breakthroughs.

Requirements

PhD in Mechanical Engineering, Aerospace Engineering, Applied Mathematics, Computational Science, or a related field such as controls, optimization, estimation, or detection algorithms.
Legal authorization to work in the U.S. is required. We will not sponsor individuals 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.
Must be 18 years or older.
You must submit your application for employment on the careers page at www.careers.gevernova.com to be considered.
At least 2 years of post-doctoral research experience in an industrial or laboratory setting with demonstrated capabilities in high-fidelity multiphysics modeling, machine learning methods, and high-performance computing.
Strong fundament knowledge of fluid mechanics, aerodynamics, turbulence, heat transfer, combustion, reactive flows etc.
Demonstrated capabilities in use of AI and scientific machine learning to automate and accelerate design, computations methods, and workflows.
Proficiency in Python, JAX, pyTorch, TensorFlow, FORTRAN, C++ etc.
Familiarity with commercial and open-source simulation tools (e.g., ANSYS, OpenFOAM, COMSOL, Abaqus).
Demonstrated experience with meshing strategies, numerical stability, and convergence analysis.
Ability to contribute to the development of research proposals to internal business units and external government agencies such as Department of Energy etc.
Proven record of innovation, as evidenced by publications, patents, or conference presentations.
Strong interpersonal and communication skills, with the ability to work across disciplines and engage with senior technical leaders and customers.
Ability to adapt to evolving project requirements and fast-paced technology development cycles.
GE Vernova will only employ those who are legally authorized to work in the United States for this opening. Any offer of employment is conditioned upon the successful completion of a drug screen (as applicable).