Research Scientist, Physics x AI

Research Scientist, Physics x AI

Here at Siemens, we take pride in enabling sustainable progress through technology. We do this through empowering customers by combining the real and digital worlds. Improving how we live, work, and move today and for the next generation! We know that the only way a business thrives is if our people are thriving. That’s why we always put our people first. Our global, diverse team would be happy to support you and challenge you to grow in new ways. Who knows where our shared journey will take you?

Transform the everyday with us!

In this role you will work onsite in our Princeton, NJ office.

We are an AI research Lab specializing in Physics x AI research. Our mission is to scale the capabilities of AI in the physical domain, encoding diverse scientific and engineering knowledge into neural networks to tackle complex, high-impact industrial and scientific problems. As an integral part of Siemens’ Data Analytics & AI organization, we drive physical AI innovation for an industrial scale.

Our team is part of Siemens Technology, Siemens’ central in-house research department. It acts as a strategic partner to support our executive units with R&D and innovation services, protects the company’s intellectual property, coordinates collaborations with top universities worldwide, and supports standardization activities in all business units and regions.

As a Physics x AI Research Scientist, you will explore and build the next generation of scalable, generalizable physics-aware foundation models. We actively welcome candidates from a broad range of backgrounds—including fluid dynamics, electromagnetics, electrical engineering, systems engineering, and biological domains such as protein folding—who are passionate about encoding physical, biological, or engineering priors into modern AI systems. You’ll focus on architectures (especially transformers) that move beyond the limitations of narrow, hard-coded models into robust solutions that generalize across geometries, conditions, and disciplines.

Your future impact areas may include:

• Systems engineering and verification workflows (from design through manufacturing)
• AI-native electronic design automation (EDA) and chip design
• Any other discipline where physical or biological priors in AI can bring breakthrough scale and generalization

A research scientist in our team will:

• Translate business needs into actionable project proposal, negotiate project terms and budget
• Steer delivery of complex, multi-national, strategic projects in cooperation with stakeholders and the project team
• Validate the market potential of new AI innovation and develop business models for products, services, and solutions.
• Drive ideas from ideation to productization with a customer mindset
• Own global Siemens cross-company technology roadmaps and shape the interfaces to other technologies
• Work with our U.S.-based and global research groups to proactively shape the strategy of our AI research and pre-development operation in the S.
• Shape the subsidies and grants portfolio for our AI research and pre-development in the U.S.
• Communicate complex technology topics to non-experts and executive decision-maker
• Conduct hands-on research and development scalable, physics-aware foundation models
• Model and encode knowledge from diverse scientific and engineering domains - including but not limited to fluid dynamics, electromagnetics, electrical engineering, biology/protein folding (excluding quantum science)
• Document and publish research, and present proposals and results confidently to both internal and external large audiences
• Proactively engage with Siemens domain experts, their customers and partners to understand real-world problems, collect requirements, and co-create innovative solutions
• Translate cutting-edge research into industrial impact, including proof-of-concept projects, identifying and closing research gaps
• Identify, adopt, and apply evolving trends in machine learning, physics-informed AI, and AI for science
• Collaborate with our interdisciplinary Princeton-based lab and contribute to Siemens’ global Data Analytics & AI network

Basic Qualifications:

• Master’s degree with relevant research/industry experience or a PhD degree in a STEM field, i.e. Computer Science, Physics, Applied Mathematics, Electrical Engineering, Mechanical Engineering, Biophysics, Bioinformatics, or similar.
• Established track record of pub…