Job Title: Simulation, Optimization and Applied AI Research Professional
Site: Princeton NJ
Hours of the Shift: 8AM- 5PM
Position Description:
In this role, you will play a key part in advancing the next-generation simulation methods and their application to design, manufacturing, commissioning and operation tools that align with strategic goals in automation, energy efficiency, and sustainability.
You will have the unique opportunity to work hands-on with proprietary simulation tools, gaining experience with cutting-edge platforms that are shaping the future of engineering innovation.
Key Responsibilities:
Research on next-generation physics-based simulation methods for design, control, manufacturing, and operations.
Integrate optimization and AI/ML-infused approaches into simulation workflows to improve modeling, manufacturability, performance prediction, reusability, and reliability analysis.
Develop digital twin applications for mechatronics products.
Experience with various physical laws (heat transfer, structures, electrical circuits, fluid dynamics, electromagnetism, ).
Domain knowledge on some of the following verticals: automotive, aerospace, manufacturing, or buildings.
Present, explain, and demonstrate technical results with customers on abstract levels in internal meetings, visits, video conferences, and external conferences.
Protect the results of your work through patent applications and publish results at conferences or in top journals.
Basic Qualifications:
Ph.D. or M.S. in Mechanical Engineering, Aerospace Engineering, Electrical Engineering, Physics, or similar, from an accredited university.
Minimum of 4 years of research or development experience in simulation, optimization and applied-AI.
Minimum of 2 years of hands-on experience in product design and operation.
Minimum of 4 years of experience in python, and C++ programming languages.
Experience working in international project teams with strong customer orientation and stakeholder management skills.
Proficiency in English (verbal & written).
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