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Siemens · 3 hours ago

Simulation, Digital Twin, and Physical AI Engineering Internship

Princeton, NJ

Internship

Hybrid

Intern

$35/hr - $47/hr

Siemens is a global technology company focused on industry, infrastructure, transport, and healthcare. They are looking for a highly motivated intern to join their Design and Simulation of Systems research group, where the intern will work on developing methods that connect simulation, data, and intelligent physical systems.

Artificial Intelligence (AI)ConsultingCyber SecurityInternet of Things

No H1B

Responsibilities

Develop physics‑based and data‑driven digital twin models for mechanical, thermal, structural, or multi‑physics systems relevant to manufacturing and infrastructure

Integrate simulation models with AI/ML components to enable perception, anomaly detection, prediction, or control of physical systems

Build simulation-to-real pipelines (e.g., domain randomization, synthetic data generation, model‑based RL)

Design and test workflows for remote asset inspection, including sensor data processing, surrogate modeling, or AI‑based defect detection

Benchmark new methods against existing tools, third‑party datasets, or field measurements

Collaborate closely with domain experts, simulation engineers, and AI researchers to deliver innovative and practical prototypes

Document methods and results, present progress to the research team, and contribute to publications where possible

Qualification

PythonMachine LearningSimulation ToolsDigital Twin ConceptsData-Driven ModelingC++Analytical SkillsInterdisciplinary CollaborationCommunicationTime Management

Required

Currently enrolled in a master's program in Mechanical, Aerospace, Electrical, Computer, Robotics Engineering, Applied Physics, Computer Science, or other from an accredited university

Experience with simulation or modeling tools (e.g., finite element, multibody, CFD, system simulation, or equivalent)

Hands‑on experience with Python and ML frameworks (PyTorch, TensorFlow, JAX, etc.)

Familiarity with data‑driven modeling methods such as neural networks, surrogate models, reinforcement learning, or digital twin concepts

Proficient in English both written and verbal

Must be located in the U.S. and legally authorized to work in the U.S. for the duration of the internship