Share this Job

Sr Research Scientist - Product Performance Modeling

Apply now »

Date: Aug 8, 2022

Location: Corning, NY, US, 14831

Company: Corning

Requisition Number: 55318

 

Corning is one of the world’s leading innovators in materials science. For more than 160 years, Corning has applied its unparalleled expertise in specialty glass, ceramics, and optical physics to develop products that have created new industries and transformed people’s lives.

At Corning, our growth is fueled by a commitment to innovation. We succeed through sustained investment in research & development, a unique combination of material and process innovation, and close collaboration with customers to solve tough technology challenges. We are a four-time National Medal of Technology winner thanks to our technology leadership and R&D environment, which attract and enable the best scientific minds in the world. This pipeline of talent has brought life-changing innovation to your fingertips for more than 160 years.

 

Position Description:

Collaborate with research, development, engineering, manufacturing, and commercial teams to support product development efforts by applying knowledge of the mechanics of materials, statistical/probabilistic modeling with software programming, and reliability engineering methods to identify/ understand/ address concerns and quantify/optimize product performance. This includes developing experimental and characterization strategies to generate data, gain deeper knowledge, with proactive problem avoidance and recommendations to improve product performance and enable efficient development of reliable products and processes across a range of technologies.

 

Responsibilities include:

  •  Work with scientists and customers to understand the physical/engineering design and process those drive the products performance, determine if the products they are developing meet the requirements, and provide guidance on optimization.
  •  Mathematical Modeling and Statistical Data Analysis: Establish modeling framework with mathematical fundamentals and advanced probability theories to represent the underlying mechanisms and related random variables that are critical for product performance. Perform complex data analysis with statistical methods to quantify the multiple factors effects and uncertainty to minimize cost and development time while maximizing performance, to predict lifetime in a variety of applications, and/or establish reliability objectives of finished product.
  •  Mechanics: Leverage understanding of fracture mechanics or mechanical structure to collaborate with glass & ceramic technical experts to enable creative coupling of physics/mechanics with statistics/modeling to design experiments, develop models, understand fundamentals, and solve problems.
  •  Software programming: If existing software is incapable, develop codes to implement the customized models and methods and create GUIs via algorithm development (combining math and science) to generate life models/ predictions and enable computing by other scientists (Matlab, Python or R).
  •  Reliability Engineering: Use methods/tools to understand needs and requirements of a product and identify potential concerns/ failure modes. Develop strategic experiments related to failure modes to generate insight into fundamentals as well as data for predictive models. Use insight to make recommendations related to product and/or process parameters that impact performance; create intellectual property.
  •  Write technical reports to capture knowledge related to work.

 

 

Hours of work/work schedule/flex-time: 40+ hours/week, 8am-5pm

 

Education and Experience (minimum required for consideration):

A Technical Master’s degree is preferred or Bachelor’s with appropriate experience.  Looking for at least 5 years’ experience in a product/process development type role.

 

Requirements:

• Advanced reliability and probability theory; Statistics & stochastic processes; Complex math modeling & data analytics; Optimization

• Complex mathematical analytics, machine learning, model calibration & validation & updating & prediction, uncertainty quantification and software (MATLAB, R, Python)

• Science education (Mechanics preferred) for Physics of Failure/ material property understanding to enable collaboration with technical experts to correctly combine test data/physical phenomena with statistical theory

• Ability to collaborate and work successfully across organizations & functions

• Critical thinking/ problem solving with ability to make connections with broad knowledge of materials, physical properties, test methods and failure mechanisms. Creative

• Excellent communication skills – verbal and written

• Results & detail oriented, Proactive, Rigorous, Self-motivated, Flexible, Multi-tasking, Honesty WANTS • Advanced software programming/development of algorithms and GUIs (R, Python, C++)

• Mechanical Engineering or related degree (minimum of a Master’s)

• Can lead design assessments and suggests design improvements

• Reliability engineering expertise to facilitate effective design assessment and optimization: define requirements, identify areas of concern, design experiments and use data to gain insight for design feedback &/or generate a life prediction (QFD, FMEA, RCA, FTA, etc.)

• Environmental stress testing methodology knowledge (temp, humidity, power, mechanical, vibration, HALT, HASS, etc.)

• Brittle Material, Glass and Ceramics knowledge

• Working knowledge of characterization techniques – how to apply and interpret results

 

We prohibit discrimination on the basis of race, color, gender, age, religion, national origin, sexual orientation, gender identity or expression, disability, veteran status or any other legally protected status.

 

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.


Nearest Major Market: Corning