Requisition Number: 75070
Corning Incorporated is hiring a
Solid Mechanics Modeling Engineer in
Corning, NY. This is a
full-time onsite role based at
Sullivan Park, Corning's flagship
R&D campus, and typically works
Monday-Friday, 40 hours per week, with flexibility as needed to support project objectives. Travel is expected to be limited, though occasional
domestic or international travel may be required.
Relocation assistance is available.
If you're an engineer who likes using
mechanics and
simulation to solve real product problems - not just run models, but influence what gets built and why it works - this role offers that reach. This position sits within Corning's
modeling organization at Sullivan Park and supports a range of businesses and technologies across
research, development, manufacturing support, and customer-facing engineering challenges. You'll apply
solid mechanics, finite element modeling, and topology optimization to understand how materials and structures behave, why they fail, and how to improve performance. In simple terms, this role helps Corning design
lighter, stronger, more reliable products by using simulation and mechanics to guide engineering decisions.
Key Responsibilities- Apply solid mechanics modeling to evaluate structural performance, identify failure modes, and improve product reliability across a range of Corning materials and applications
- Use finite element analysis (FEA) to support product design, failure analysis, manufacturing challenges, and process or design improvements
- Apply topology and shape optimization methods to improve structural efficiency, reduce weight, and maintain required stiffness and performance
- Develop, adapt, or apply modeling and analytical tools to build deeper understanding of material and structural behavior, particularly for brittle materials
- Design and interpret experiments that validate models and support technical recommendations
- Provide technical guidance on mechanical testing, measurement methods, and model validation
- Partner with cross-functional teams across Research, Development, Manufacturing, and business-facing groups to solve product and engineering challenges
- Communicate findings through technical reports, presentations, and invention disclosures
Minimum Qualifications and Skills- M.S. or Ph.D. in Mechanical Engineering, Civil Engineering, Materials Science, or a related technical field
- 3+ years of relevant professional experience acquired after degree completion; postdoctoral research experience may also be considered
- Experience developing constitutive material models and characterization approaches for brittle materials, supported by hands-on experience with materials testing, especially strength and fracture testing
- Strong knowledge of solid mechanics, including topology and shape optimization methods
- Ability to translate complex engineering problems into mathematical or numerical models, design experiments to validate them, and develop technically sound recommendations
- Strong background in structural finite element analysis, using tools such as Abaqus, Tosca, ANSYS, or equivalent software, along with programming and scripting skills in Python, MATLAB, or C++
- Strong written and verbal communication skills and the ability to work effectively across globally distributed teams
Preferred Qualifications and Skills- Experience with open-source FEA or multiphysics tools, such as MOOSE
- Experience in process engineering, product engineering, or manufacturing support, including product performance evaluation and technical data analysis
- Broad knowledge of mechanical and materials testing techniques, along with experience using structured experimental and problem-solving methods such as DOE, MEE, Six Sigma DMAIC, or similar approaches
- Demonstrated ability to manage multiple technical projects and work effectively across diverse stakeholders and cultures
This position supports immigration sponsorship.The range for this position is $96,913.00 - $133,256.00 assuming full time status. Starting pay for the successful applicant is dependent on a variety of job-related factors, including but not limited to geographic location, market demands, experience, training, and education.
