Research Scientist in AI Empowered Materials Engineering

Research Scientist in AI Empowered Materials Engineering

Description -

HP’s Digital Twin group with the Additive Manufacturing Software Global Business Unit is seeking passionate and creative Research Scientist to solve the toughest and most relevant problems in additive manufacturing: design and then fabricate new materials on the fly, enabling new types of predictable and consistent performance and new functionalities never seen by the industry. 

This Digital Twin group grows out of HP Labs, HP’s advanced research organization. This group holds 100 granted patents, dozens of publications covering novel material design and modeling, Physics Informed AI and computational materials engineering, in addition to having released commercial software product actively used by HP’s customers. We contribute to fundamental research in the field of Physics Informed AI in collaboration with leading U.S. universities sponsored by federal research agency.  We champion for open innovation; we actively open-source Physics Informed AI research software to drive up Digital Twin technology creation and application. 

This position is situated in Palo Alto, California, at the heart of the Silicon Valley. We also have flexibilities to consider other U.S. West Coast sites. You will be collaborating with some of the brightest minds to develop Digital Twins that accurately virtualize manufacturing processes and the resulting end materials. These Digital Twins are anchored on a computational sciences core while calibrated and accelerated by AI. 

Scope and Responsibilities
1.    Working with the internal group together to develop, implement and validate novel Digital Twin algorithms synthesizing computational materials engineering and AI. 
2.    Collaborate with university partners on Physics Informed AI. One example topic is AI-based surrogate modeling that accelerates physics simulation. 
3.    Collaborate with industrial partners on open-source efforts. 
4.    Publish at leading conferences and journals. 

Qualifications.

The approach of synthesizing computational sciences and AI is emergent. We look for candidate that has both a solid relevant technical foundation and strong learning capability to quickly pick up the rest.  If you can check off the major items listed below, we would love to hear from you!

1.    MS degree (PhD preferred) in computational science/engineering (e.g., computational physics, computational mechanical engineering, computational materials engineering), computer science, mathematics or related technical field or equivalent experience. Published papers in scientific computing (with AI application is big plus).   
2.    Demonstrated capability in developing, implementing, and validating complex material models. 
3.    Strong C++ programming skills for physics simulation solver development. Familiarity with simulation tools (opensource or commercial) for nonlinear analysis. 
4.    Knowledge of deep learning architectures and machine learning techniques (e.g., graph networks, time-series modeling, etc.). Experiences with deep learning frameworks such as PyTorch.
5.    Good python programming skills. 

Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. The typical base pay range for this role across the U.S. is $118K - $175K annually with additional opportunities for pay in the form of bonus and/or equity. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process.

Job -

Engineering

Schedule -

Full time

Shift -

No shift premium (United States of America)

Travel -

Relocation -

Equal Opportunity Employer (EEO) - 

HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s).

Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence.

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