Lead Scientist - Computational Materials Scientist – High Temperature Metallic Materials

GE Aerospace

Website: geaerospace.com
Job details:
Job Description Summary

Activities aimed at proving a concept to be valid or technically feasible by the application of scientific and engineering methodologies. Work in this family typically has the objective of demonstrating through test or analyses the performance and implementation potential of a concept

Impacts departmental operations and responsible for planning/execution. The role has some autonomy but is focused on execution of activities within an operating discipline covered by standard functional practices and procedures. Some judgment may be required but this is typically with guidance.

Job Description

Site Overview

Established in 2000, the John F. Welch Technology Center (JFWTC) in Bengaluru is our multidisciplinary research and engineering center. Engineers and scientists at JFWTC have contributed to hundreds of aviation patents, pioneering breakthroughs in engine technologies, advanced materials, and additive manufacturing.

Role Summary / Purpose

GE Aerospace invites applications from driven and exceptional Computational Materials Scientists to accelerate the discovery, development, and deployment of novel high-temperature metallic materials and processes. Applications include, but are not limited to:

• High-performance structural materials for aeroengines and aerospace applications
• Materials and processes for both conventional and additive manufacturing
  
  

This role is responsible for developing, implementing, and validating models that describe alloy chemistry, process, structure, property correlations in high-temperature metallic materials, enabling physics and data-informed materials design and deployment in critical GE Aerospace technology areas.

Essential Responsibilities

Computational methods and modeling

Develop and apply physics-based and data-driven models to establish quantitative, usable correlations between chemistry → processing → structure → properties in high-temperature metallic materials.

Model microstructural evolution and mechanical behavior under manufacturing as well as service-relevant conditions (e.g., high temperature, cyclic loading, corrosive, erosive, environments).

Discovery, development, and deployment

Drive problem solving across the spectrum of discovery, development, and deployment of high-performance alloys and processes, including alloy design, process optimization, and performance prediction.

Translate model insights into actionable design rules and process windows for engineering teams.

Integration of physics and data

Combine thermodynamics, physical metallurgy, and mechanics with computational and machine learning approaches to accelerate materials design and qualification.

Develop digital workflows and tools for rapid materials down-selection and optimization.

Collaboration and business impact

Network across GE Aerospace to understand critical materials and processing challenges, define problem statements, and build and execute technical redressal plans.

Work closely with experimental, processing, and design teams to plan validation experiments, interpret results, and refine models.

Technology leadership and thought leadership

Maintain constant awareness of mega-trends and the materials solutions required to enable them.

Contribute to a strong publication and/or patent portfolio, and present work internally and externally to establish technical leadership.

Qualifications / Requirements

• Doctorate degree or Masters degree with 5 year of relevant experience in Metallurgy, Materials Science, Physics, or a closely related field, with 2+ years research experience in structure–property correlations in metallic materials
• Strong knowledge of thermodynamics, physical metallurgy, mechanical behavior, and materials processing, particularly for high-temperature alloys.
• Direct experience with computational methods applied to metallic materials, such as:
• Thermodynamic and kinetic modeling (e.g., CALPHAD, phase-field, diffusion models)
• Microstructure and property modeling (e.g., crystal plasticity, micromechanics, fatigue/creep life prediction)
• Mesoscale and atomic scale modeling (e.g., Discrete Dislocation Dynamics, Molecular Dynamics)
• Data-driven or machine learning approaches for materials design and optimization
• Demonstrated publication and/or patent record in relevant areas
• Demonstrated ability to provide clear past examples of:
• Innovative thinking and implementation of ideas
• Application of rigorous research methodologies
• Challenging scientific theory and pushing the envelope of understanding
• Strong teaming skills and ability to work with a wide range of technical teams and projects
• Excellent oral and written communication skills.
  

Desired Characteristics

Deep understanding of chemistry–processing–structure–property relationships in nickel-base, titanium-base, cobalt-base and/or ferrous alloys for high-temperature service.

Expertise in microstructural analysis and representation, and ability to connect experimental characterization with computational predictions.

Ability to thrive in a fast-paced, cross-functional research environment, balancing exploratory research with delivery on business-critical milestones.

Additional Information

Relocation Assistance Provided: Yes Click on Apply to know more.