Post Doctoral Fellow Materials
GE Vernova · Posted Oct 8
Power generation, wind turbine, grid solution, and electrification services
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About the role
GE Vernova Advanced Research is seeking a Postdoctoral Research Fellow to advance its computational and experimental capabilities, bridging fundamental materials modeling and industrial application. The role applies multiscale physics to predict the performance and degradation of high-temperature structural materials such as Ni-based superalloys and Thermal Barrier Coatings (TBCs), as well as other energy-related materials. The fellow will integrate simulation insights with experimental validation, use AI/ML to map processing-structure-property relationships, and support optimization of existing materials for critical supply chains and design of novel manufacturing pathways, in a fixed term position for 9 months.
What you will do
- Develop and execute continuum-scale models to simulate material performance, transport phenomena, and degradation kinetics.
- Partner with laboratory teams to characterize material properties, validate model inputs, and correlate simulation predictions with empirical data from in-house tests.
- Apply your knowledge in Mechanical & Materials engineering to work on innovative solutions for the GE Vernova product portfolio.
- Learn required tools/processes and perform advanced simulations, validating models against published external results and in-house experimental data.
- Deliver on assigned project tasks with minimal guidance, document results, and provide actionable insights for material optimization.
- Collaborate with the team to improve materials management, evaluate existing materials for critical supply chains, and enhance sustainability for GE Vernova products.
- Perform literature surveys and assess the state-of-the-art landscape in material technologies, design, and manufacturing to guide R&D project direction.
- Apply AI/ML techniques to map processing-structure-property relationships to accelerate the discovery and improvement of advanced materials.
- Utilize atomistic simulations as a complementary tool to resolve fine-scale mechanisms that inform and refine larger-scale models.
- Apply systems thinking to understand the impact of material behavior at the component and system levels and actively participate in team efforts to achieve collective project goals.
Skills used in this role
What the employer is looking for
- Education: Recently completed Ph.D/Submitted Ph.D Thesis, in Materials Science, Metallurgy, or a related field ing
- Modeling Expertise: Advanced proficiency in continuum modeling software, specifically COMSOL Multiphysics, and experience with other relevant commercial or open-source simulation packages.
- Demonstrated experience in property prediction models and thermodynamic/kinetic modeling (e.g., CALPHAD).
- Proficiency in Python for scientific programming, data processing, and model automation.
- Experience applying AI/ML techniques for material property prediction and design optimization.
- Familiarity with atomistic simulation methods (e.g., DFT, MD) to supplement continuum studies.
- Experimental Background: Proven experience in a laboratory setting with the ability to interpret characterization data to inform modeling parameters.
- Domain Knowledge: Solid foundation in metallurgy and high-temperature materials. Familiarity with energy materials, fuel cells, or energy storage technologies is an asset.
- Expertise in material design and manufacturing processes.
- Communication: Strong ability to collaborate across multidisciplinary teams and articulate complex technical findings to diverse stakeholders.
- Excellent oral and written communication skills
- Demonstrated ability to work independently and in a team environment and accountability/ownership of assigned tasks
- Demonstrated ability to take up challenging assignments and deliver.
- Passion to innovate and creative problem solving
- Ability to do a State-of-the-Art Survey on and awareness/engagement with leading research groups globally in the assigned areas and synthesis the findings.
Preferred qualifications
- Experience with advanced modeling techniques such as phase-field or crystal plasticity.
- Understanding of challenges related to material availability and design strategies for critical supply chains.
- Self-motivated with a strong track record of peer-reviewed publications and conference presentations.
- Demonstrated ability to work effectively in a team-based environment, with a commitment to cross-functional collaboration and systems-level problem solving.
Benefits and support
- Compensation and benefits are detailed in the job posting
About GE Vernova
GE Vernova Inc. is a global energy company that provides equipment, services, and software to generate, transfer, orchestrate, convert, and store electricity. Operating through its Power, Wind, and Electrification segments, the company supports a broad customer base across more than 100 countries in powering economies and driving the energy transition. Formed as part of the strategic spin-off of General Electric's energy portfolio, GE Vernova is dedicated to electrifying and decarbonizing the world.
- Industry
- Energy
- Company size
- 75000+ employees
- Founded
- 2024
- Location
- Cambridge, Massachusetts, USA
- Funding stage
- Public Company
Leadership
Chief Executive Officer and President
Stephen F. Angel
Chairman of the Board
Lola Lin
Chief Legal Officer and Secretary
Roger Martella
Chief Corporate Officer, Chief Sustainability Officer & Head of Global Government Affairs
Eric Gray
CEO, Power Segment
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