Post-Doctoral Fellow - Materials Science

RE1055 GE Renewable Energy Technologies Private Limited; Bengaluru; On-site; INR 1,200,000 - 1,600,000; Full time

Job summary

GE Vernova Advanced Research in Bengaluru seeks a Postdoctoral Research Fellow to bridge fundamental materials modeling with industrial application. You will apply multiscale physics to predict performance and degradation of Ni-based superalloys, TBCs, and energy materials, integrating simulations with experiments to drive next-generation manufacturing pathways.

The fixed-term 9-month position emphasizes AI/ML mapping of processing-structure-property relationships and collaboration across

Qualifications

• Ph.D./Submitted Ph.D. in Materials Science, Metallurgy or related field (within 11 months of defense).
• Advanced proficiency in continuum modeling software (COMSOL) and CALPHAD-based thermodynamic/kinetic modeling.
• Proficiency in Python for scientific programming and data processing.
• Experience with AI/ML for property prediction and design optimization.

Responsibilities

• Develop and execute continuum-scale models to simulate material performance and degradation.
• Collaborate with lab teams to characterize properties and validate model inputs.
• Integrate simulation insights with experimental data to guide material development.
• Apply AI/ML to map processing-structure-property relationships for new materials.
• Publish findings and contribute to team-driven R&D objectives.

Skills

Multiscale modeling

COMSOL Multiphysics

Python for scientific programming

AI/ML for material design

DFT/MD atomistic methods

Data processing & automation

Discipline collaboration

Education

PhD in Materials Science/Metallurgy or related

Tools

COMSOL Multiphysics

CALPHAD

Job description

Job Description Summary

GE Vernova Advanced Research is seeking a motivated Postdoctoral Research Fellow to advance our computational and experimental capabilities. This role focuses on bridging the gap between fundamental materials modeling and industrial application. The successful candidate will apply multiscale physics to predict the performance and degradation of high-temperature structural materials, including Ni-based superalloys and Thermal Barrier Coatings (TBCs), as well as various energy-related materials. The role involves integrating simulation insights with experimental validation to drive the development of next-generation materials, including the optimization of existing materials for critical supply chains and the design of novel manufacturing pathways. This is a fixed term position for 9 months.

Job Description

This role focuses on bridging the gap between fundamental materials modeling and industrial application. The successful candidate will apply multiscale physics to predict the performance and degradation of high-temperature structural materials, including Ni-based superalloys and Thermal Barrier Coatings (TBCs), as well as various energy-related materials. The role involves integrating simulation insights with experimental validation to drive the development of next-generation materials, including the optimization of existing materials for critical supply chains and the design of novel manufacturing pathways.

Roles and Responsibilities

• 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.

Required Qualifications

Education: Recently completed Ph.D/Submitted Ph.D Thesis, in Materials Science, Metallurgy, or a related field ing (< 11 months post completion of Ph.D Defense) 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.

Desired Characteristics

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.

Additional Information

Relocation Assistance Provided: Yes Addressing the climate crisis is an urgent global priority and we take our responsibility seriously. That is our singular mission at GE Vernova: continuing to electrify the world while simultaneously working to help decarbonize it. If we want our energy future to be different…we must be different. Our mission is embedded in our name. We retain our treasured legacy, “GE,” in our name as an enduring and hard-earned badge of quality and ingenuity. “Ver” / “verde” signal Earth’s verdant and lush ecosystems. “Nova,” from the Latin “novus,” nods to a new, innovative era of lower carbon energy that GE Vernova will help deliver. Together, we have The Energy to Change the World. www.gevernova.com