Corning Research Center India is seeking a technically exceptional and innovative
Senior Scientist
to join the team in Pune, India. The ideal candidate will apply engineering knowledge, advanced numerical methods, and computational modeling techniques to solve challenging problems related to product performance and manufacturing processes across Corning s diverse portfolio of materials and technologies.
We are looking for a creative, out-of-the-box thinker who can work independently and collaborate effectively with global, multidisciplinary teams to deliver high-impact, innovative, and life-changing solutions. This role requires expertise in solid mechanics, Finite Element Analysis (FEA), and modeling techniques, as well as strong programming skills.
Key Responsibilities:
- Develop, validate, and apply numerical models to solve problems related to dynamic impact, nonlinear FEA, fracture mechanics, and applied mechanics.
- Collaborate with cross-functional teams, including experimentalists, researchers, scientists, and project leaders located globally, to address research and development challenges.
- Create models using appropriate numerical methods and software and expand modeling capabilities as required.
- Translate real-world problems into solvable modeling objectives and provide actionable insights.
- Communicate and present project updates to stakeholders across global locations.
- Document results and findings via internal reports and external publications.
- Stay at technological forefront in modeling, simulation, and applied mechanics.
Required Skills:
- Strong background in
solid mechanics
and Finite Element Analysis (FEA)
with a deep understanding of solid mechanics concepts and theory. - Hands-on experience with commercial FEA software, including (but not limited to)
ABAQUS, LS-DYNA, ANSYS Mechanical, MATLAB,
and Tecplot
. - Expertise in modeling dynamic impact problems, material nonlinearities, and fracture mechanics.
- Proficiency in programming languages such as C/C++, Unix, Shell, and Python.
- Strong analytical, diagnostic, and problem-solving skills.
- Ability to break down complex real-world problems into solvable modeling objectives.
- Versatility in adapting to various technology areas; a balanced combination of technical depth and breadth.
- Self-motivated with a long-term interest in technical growth.
Desired Skills:
- Experience with
open-source FEA software frameworks
, such as MOOSE or FEniCS
, is ana dded advantage - Exposure to
Artificial Intelligence (AI), Machine Learning (ML), and Data Analytics
techniques particularly as applied to modeling, simulation, or materials science. - Familiarity with
statistical methods, machine learning frameworks
(e.g., TensorFlow, PyTorch), or
data visualization tools
. - Experience working in an
industrial R&D environment
. - Knowledge of
data-driven modeling, optimization, or predictive analytics
. - Flexibility to thrive in a dynamic work environment and adapt to changing priorities.
- Ability to integrate physics-based models with data-driven approaches to enhance predictive capabilities.
Soft Skills:
- Highly collaborative and capable of fostering open engagement with colleagues to achieve project goals.
- Strong technical curiosity with a desire to continually learn and grow in diverse technology areas.
- Ability to translate complex technical concepts into simplified explanations for broader audiences.
- Self-driven with a proven ability to manage independent workstreams.
- Effective communication skills for remote collaboration with global teams via phone and video calls.
Education and Experience:
-
PhD, Master s, or Dual Degree
in Mechanical Engineering, Civil Engineering or Materials Science with an emphasis on solid mechanics and Finite Element Analysis from IITs, IISc, or reputed foreign universities - Candidates with
more than 4 years of relevant work experience
post-Masters/Dual Degree or more than 2 year of experience
post-PhD are welcome to apply.
Travel:
- Occasional travel to global locations to collaborate with colleagues in research, development, engineering, and manufacturing teams.
Work Flexibility:
- Option to work-from-home
up to 2 days per week.
