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Power System Control and Simulation Internship

Siemens Foundational Technologies is seeking a highly motivated and technically strong Power System Simulation Intern to join the Autonomous Controls and Operations research group in Princeton, NJ for a 3-6 month internship. This role is focused on dynamic modeling and simulation of inverter-based resources (IBRs) in PSS®E, with particular emphasis on Grid-Forming (GFM) and Grid-Following (GFL) inverter technologies, wind energy system modeling, and the development and application of user-defined models (UDMs) for power system dynamic studies.

This internship is well suited for candidates with strong experience in power system dynamics, renewable generation modeling, and simulation tool development workflows. The selected candidate will contribute to advanced simulation studies relevant to modern power systems with increasing penetration of inverter-based and renewable resources. The role includes model implementation, validation, automation, and technical analysis in support of industrial research applications.

This role you would work on-site in Princeton, NJ.

Key Responsibilities

• Develop, implement, compile, integrate, and validate PSS®E user-defined models (UDMs) in PSS®E for advanced inverter control, renewable generation, and dynamic system studies, e.g., WECC generic renewable energy models, especially wind models, for utility-scale power system simulations
• Model and simulate wind energy conversion systems and wind power plants, including different wind generation technologies and control representations used in stability studies
• Use Fortran-based model development workflows and compiler environments to build and maintain PSS®E dynamic model libraries
• Perform dynamic simulations in PSS®E for inverter-based resources, including detailed investigation of GFM inverter behavior under disturbances and varying grid conditions to evaluate transient stability, dynamic performance, control interactions, and system strength impacts associated with inverter-based resources
• Develop Python-based tools and scripts for simulation automation, batch execution, output processing, data analysis, and result visualization
• Support model benchmarking, validation, and comparison against expected dynamic behavior or reference implementations
• Prepare technical documentation summarizing model assumptions, parameterization, simulation methodology, and findings
• Collaborate with Siemens researchers and engineers on advanced power system studies involving renewable integration and inverter-dominated grids

Basic Qualifications

• Currently enrolled in an MS or PhD program in Electrical Engineering, Power Systems Engineering, or similar in an accredited university.
• Hands-on experience with PSS®E dynamic simulations, including dynamic case setup, disturbance definition, model execution, and response evaluation
• Familiarity with Fortran programming and compiler toolchains used for PSS®E model compilation and integration
• Proficiency in Python for engineering workflows, simulation automation, and technical data analysis
• Background in wind energy technologies, including modeling and simulation of different wind power generation types
• Understanding of Grid-Forming (GFM) and Grid-Following (GFL) inverter control concepts and dynamic behavior
• Solid foundation in power system dynamics, stability, and control
• Proficiency in English both written and verbal
• Authorized to work in the United States without corporate sponsorship now and in the future

Preferred Qualifications

• Experience developing, modifying, or working with user-defined models (UDMs) in PSS®E
• Experience with WECC generic renewable models, particularly wind turbine / wind plant models
• Experience using Python libraries such as NumPy, pandas, and Matplotlib for analysis and visualization
• Ability to work effectively in a technically deep, research-oriented, and collaborative environment

Export Control / Eligibility Statement

A successful candidate must be able to work with controlled technology in accordance with U.S. Export Control Law. U.S. Export Control laws and applicable regulations govern the distribution of strategically important technology, services, and information to foreign nationals and foreign countries. Siemens may require candidates under consideration for employment opportunities to submit information regarding citizenship status to allow the organization to comply with specific U.S. Export Control laws and regulations. Additional information can be found at:

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 and advanced healthcare, we create technology with purpose, adding real value for customers.

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You'll Benefit From

Siemens offers a variety of health and wellness benefits to our employees. Details regarding our benefits can be found here: The pay range for this position is $35-$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.

Equal Employment Opportunity Statement

Siemens is an Equal Opportunity Employer encouraging inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to their race, color, creed, religion, national origin, citizenship status, ancestry, sex, age, physical or mental disability unrelated to ability, marital status, family responsibilities, pregnancy, genetic information, sexual orientation, gender expression, gender identity, transgender, sex stereotyping, order of protection status, protected veteran or military status, or an unfavorable discharge from military service, and other categories protected by federal, state or local law.

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Application Deadline

This role will be posted for a minimum of five (5) days from the original posting date. The posting timeline may change based on applicant volume to ensure we attract and consider a strong and representative candidate pool.

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