Job Description SummaryAs a member of the probabilistic design team, you will contribute to the development of state-of-the-art probabilistic methods, engineering design tools, solving challenging real-world industry problems in the area of metamodeling/surrogates, machine learning, model calibration and validation, uncertainty quantification, optimization and robust design, inverse modeling, engineering analysis model validation for GE Aerospace and U.S. government projects.Job DescriptionRoles and ResponsibilitiesThe successful candidate for this position will participate in developing state-of-the-art probabilistic and machine learning methods and tools to deliver world-class solutions for new product introduction (NPI), services, energy transition, and the future of flight throughout the GE Aerospace company. You will also work with U.S. government partners to solve some of the most pressing global challenges. You will work in a multi-disciplinary team contributing to the applications for performing prognostics and optimizing structures and systems under uncertainty for performance, weight, and cost. Applications include turbo machinery, material and mechanical systems, additive manufacturing, sustainable aviation fuel, hybrid electric propulsion, and hydrogen-powered flight.You will:Collaborate with GE Aerospace design and services communities in the development of methods for probabilistic design, machine learning and optimizationApply probabilistic design, machine learning and optimization methods to real-world industrial applications for NPI design and Services maintenance planning for GE Aerospace businessImplement probabilistic design, machine learning and optimization methods into GE internal design and services tools.Train and coach GE engineers on probabilistic and machine learning methods and toolsLead and manage projects, people and fundingQualifications / RequirementsDoctorate degree in Mechanical Engineering, Aerospace Engineering with at least 3 years industrial experience, or related discipline OR Master’s degree in Mechanical Engineering, Aerospace Engineering, or related discipline with at least 8 years industrial experienceExperience in probabilistic design, machine learning, and/or optimization of engineering components and systemsFundamental knowledge in probabilistic methods, machine learning, Bayesian methods, and optimization applied to engineering design problemsExperience with leading government programs and proposal writing.Fundamental understanding of solid mechanics and tools used in structural analysis such as ANSYS or similar FE softwareAbility to develop, modify and utilize custom computer codes in various languages such as Python, C++, Matlab, Visual Basic, Perl, R, etcLegal 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 openingMust be willing to work onsite in Niskayuna, NYDesired CharacteristicsIn-depth understanding and methods development experience in dynamic Bayesian networks, Bayesian networks, physics-base/physics-informed forecasting, time-series modeling, image-based surrogates, probabilistic deep learning, transfer learning, physics discovery, uncertainty quantification, model calibration, verification & validation, DOE/DACE, metamodeling, sensitivity analysis, and inverse designExperience in solving complex engineering problems using probabilistic and machine learning methods aboveExperience with mechanical design and analysis methodsExperience with software developmentExperience with fracture mechanicsDemonstrated interpersonal, leadership and communication skills in a global team environmentStrong interpersonal skills and analytical skillsAbility to work across all functions/levels as part of a teamAbility to work under pressure and meet deadlinesExcellent written and verbal communication skillsThe base pay range for this position is 90,000 - 175,000 USD Annually. The specific pay offered may be influenced by a variety of factors, including the candidate’s experience, education, and skill set. This position is also eligible for an annual discretionary bonus based on a percentage of your base salary.This posting is expected to close on September 25, 2024Healthcare benefits include medical, dental, vision, and prescription drug coverage; access to a Health Coach, a 24/7 nurse-based resource; and access to the Employee Assistance Program, providing 24/7 confidential assessment, counseling and referral services. Retirement benefits include the GE 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 planning consultants. Other benefits include tuition assistance, adoption assistance, paid parental leave, disability insurance, life insurance, and paid time-off for vacation or illness.General Electric Company, Ropcor, Inc., their successors, and in some cases their affiliates, each sponsor certain employee benefit plans or programs (i.e., is a “Sponsor”). Each Sponsor reserves the right to terminate, amend, suspend, replace, or modify its benefit plans and programs at any time and for any reason, in its sole discretion. No individual has a vested right to any benefit under a Sponsor’s welfare benefit plan or program. This document does not create a contract of employment with any individual.This role requires access to U.S. export-controlled information. If applicable, final offers will be contingent on ability to obtain authorization for access to U.S. export-controlled information from the U.S. Government.Additional InformationGE offers a great work environment, professional development, challenging careers, and competitive compensation. GE is anEqual Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.GE 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). Relocation Assistance Provided: Yes