Lead Informatics Engineer

GE Vernova•Greenville, NC

3d•Hybrid

About The Position

The Material Behaviors & Informatics Engineer will develop and deploy computational, statistical, and probabilistic frameworks towards the prediction, optimization, and characterization of next-generation alloys and chemistries for gas turbine applications.

Requirements

Bachelor’s, Master’s, or Ph.D. degree in Materials, Metallurgical or Mechanical Engineering, Data or Computer Science, or related discipline from an accredited college or university.
At least 4 years relevant experience in materials.
Strong foundation in materials science fundamentals.
Ability to access and handle US Export Controlled information.
Ability to work hybrid/onsite out of Greenville, SC office.

Nice To Haves

Strong foundation in structure-property-behavior relationships of alloys like nickel, steel and materials like ceramics and their strengthening mechanisms.
Familiarity with modeling of mechanical and physical properties of these materials.
Knowledge of statistical characterization methods such as Gaussian and Bayesian distributions.
Knowledge of computational materials science, and tools such as Calphad, Crystal Plasticity, Density Functional Theory.
Familiarity with material testing, characterization, and interpretation of results.
Experience in developing statistical/probabilistic models for regression, optimization, and prediction related tasks.
Familiarity of translating research into practical engineering applications.
Familiarity with relevant python libraries for machine learning, optimization, regression, and visualization (scikit-learn, pytorch, scipy, seaborn, matplotlib, etc.)
Familiarity with different categorical and regression-based machine learning algorithms and knowledge of their strengths and limitations
Familiarity with supervised, semi-supervised, and un-supervised machine learning algorithms
Familiarity with multi-objective optimization
Knowledge of computer vision fundamentals (object detection, segmentation, classification, tracking) and models
Strong organizational skills and demonstrated ability to drive projects to completion.
Effective at working independently on complex tasks and managing multiple priorities under tight deadlines.
Strong verbal and written communication skills.
Ability and willingness to work effectively as part of a high performance, cross-functional team to drive impactful results.
Strong people skills to collaborate with team members and support tasks.

Responsibilities

Design and deploy robust computational, statistical, and probabilistic models to predict material properties and behavior from existing datasets, field performance data, and scientific literature
Use data-driven techniques to identify new next-generation alloys and optimize known materials and material testing programs
Create and manage material data bases
Define the technical roadmap for materials informatics initiatives, establishing best practices and methodologies
Partner with materials engineers and design engineers to translate computational insights into practical applications
Provide mentorship to team members, fostering a culture of innovation and continuous learning
Present findings and recommendations to technical and business stakeholders, translating complex analyses into strategic decisions

Benefits

medical, dental, vision, and prescription drug coverage
access to Health Coach from GE Vernova, a 24/7 nurse-based resource
access to the Employee Assistance Program, providing 24/7 confidential assessment, counseling and referral services
GE Vernova Retirement Savings Plan, a tax-advantaged 401(k) savings opportunity with company matching contributions and company retirement contributions, as well as access to Fidelity resources and financial planning consultants
tuition assistance
adoption assistance
paid parental leave
disability benefits
life insurance
12 paid holidays
permissive time off