Job ID

498868

Posted since

12-Mar-2026

Organization

Foundational Technologies

Field of work

Internal Services

Company

Siemens Corporation

Experience level

Student (Not Yet Graduated)

Job type

Full-time

Work mode

Office/Site only

Employment type

Fixed Term

Location(s)

• Princeton - - United States of America

Inverse Modeling for Dynamical Systems and Machine Learning Internship

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. We do this through empowering customers by combining the real and digital worlds, thereby 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!

Company Overview

Siemens Foundational Technology (FT) is the central R&D department of Siemens and thus has a key role in shaping the future of our Simulation and Digital Twin technology. FT acts as a strategic partner to support the executive units of Siemens. In consequence, the main research focus is on future technologies for industry, infrastructure, mobility, and healthcare. We are looking for an Intern who will work within our Design and Simulation of Systems research team in Princeton, NJ.

In this role you will work on-site in Princeton, NJ. The position is a full-time position for at least 3 months.

Role Summary

In this internship, we are looking for a motivated and talented student with experience in simulation, machine learning, and optimization methods. You will build engineering analysis and optimization workflows with the help of traditional numerical methods and machine learning methods. The internship provides a unique experience to contribute to innovative industrial applications while mentored by experienced research professionals in an international setting. The position is a full-time role for at least 3 months with option of a hybrid arrangement if appropriate.

Key Responsibilities

• Explore and build upon the latest ML-based inverse modeling approaches for dynamical systems observed through multi-dimensional time series
• Integrate models into high-order workflows and pipelines, such as optimization and uncertainty quantification assessments.
• Test and benchmark the created models with third-party or publicly available data.
• Collaborate with domain and subject matter experts who seek to design and develop novel solutions for challenging real-world industrial problems.
• Document learnings and project progress and regularly present results to the research and consulting team. Publication of results is encouraged where possible.

Education and Experience

• To be considered for this role, you must be enrolled in a Computer Science, Electrical Engineering, Statistics, Applied Mathematics or a similar Engineering PhD program working on the use of AI approaches for Inverse Modeling of Dynamical Systems.

Basic Qualifications

• Experience with setting ML model training and testing/evaluating ML models.
• Graduate level courses in Statistics, Data Modeling and AI
• Understanding of the latest ML approaches and architectures.
• Clear understanding of transforms such as Fourier and Wavelet
• Hands-on experience with software development in Python.
• Proficiency in English (verbal & written).

Preferred Skills

• Ability to quickly learn to use new technologies and frameworks.
• Flexibility and resourcefulness to work in a growing, dynamic, interdisciplinary team of specialists.
• Ability to work independently and manage time effectively Hands-on experience with Scientific Machine Learning.
• Familiar with Linux systems and computational clusters (CPU/GPU).
• Basic experience in version control systems and agile development, among others.
• Real-world problem-solving and a hands-on, can-do mentality.
• Eager to present your proposals and results in front of a big audience.

Work setting

The position does require the person to be in the United States of America and hold a valid work permit for the US.

• Ability to work independently and as part of a team.
• Strong communication skills, both written and verbal
• Experience with various Neural Network encodings such as Graph Neural Networks.
• Experience with geometric representations, B-Rep, Voxels, CSG, Implicit, Design by Code, etc.
• Knowledge of advanced statistical methods and data visualization techniques.
• Strong organizational and project management skills.

About Siemens:

We are a global technology company focused on industry, infrastructure, transport, and healthcare. From more resource-efficient factories, resilient supply chains, and smarter buildings and grids, to sustainable transportation as well as advanced healthcare, we create technology with purpose adding real value for customers. Learn more about Siemens here.

Our Commitment to Equity and Inclusion in our Diverse Global Workforce:

We value your unique identity and perspective. We are fully committed to providing equitable opportunities and building a workplace that reflects the diversity of society, while ensuring that we attract the best talent based on qualifications, skills, and experiences. We welcome you to bring your authentic self and transform the everyday with us.

#LI-JS

#LI-REMOTE

#NSBE26

You’ll Benefit From
Siemens offers a variety of health and wellness benefits to our employees. Details regarding our benefits can be found here: https://www.benefitsquickstart.com/siemens/index.html
The pay range for this position is $32-$47 per hour. The actual wage offered may be lower or higher depending on budget and candidate experience, knowledge, skills, qualifications and premium geographic location.