Internship in Foundation Models and Optimization for Power Grids 80 - 100% (f/m/d)

Hitachi; Schweiz; Presencial; CHF 20 000 - 27 000; Tempo integral

Resumo da oferta

The System and Automation team at Hitachi Energy’s Swiss research center seeks an intern student with expertise in numerical optimization and machine learning to advance real-time power grid monitoring. You will work under senior researchers, applying ML to accelerate numerical algorithms for reliable, efficient grid operation.

Six-month internship. Enthusiastic candidates from an MSc program in EE, CS, or Applied Math with Python/C++/MATLAB and PyTorch experience are welcome.

Qualificações

• Enrolled in an MSc program in Electrical Engineering, Computer Science, Applied Mathematics, or a related field.
• Strong background in numerical optimization.
• Good knowledge of machine learning and deep learning.
• Experience with PyTorch or similar deep learning frameworks.
• Experience in Python or C++ programming and MATLAB.

Responsabilidades

• Contribute to research activities on ML-based methods for power system monitoring
• Investigate, deploy and refine foundation models for representing power grid topology, measurements, and operating conditions
• Combine ML-driven methods with numerical optimization and power system physics
• Evaluate the proposed methods through simulation studies and benchmarking
• Report and disseminate results within the team, write technical documentation, and contribute creative ideas towards industrial implementation

Conhecimentos

Numerical optimization

Machine learning

Python

C++

MATLAB

PyTorch

English

Formação académica

MSc in Electrical Engineering

MSc in Computer Science

MSc in Applied Mathematics

Ferramentas

Python

MATLAB

Descrição da oferta de emprego

Location:

Baden-Daettwil, Aargau, Switzerland

Job ID:

R0145074

Date Posted:

2026-09-23

Company Name:

HITACHI ENERGY LTD

Profession (Job Category):

Administration & Facilities

Job Schedule:

Full time

Remote:

No

Job Description:

The opportunity

The System and Automation team at the Swiss research center is looking for an intern student with expertise in numerical optimization and machine learning (ML) to contribute to cutting-edge developments for modern power grid operation. The internship will focus on applying ML techniques to accelerate and improve numerical algorithms for real-time power system monitoring, enabling more reliable, efficient, and resilient grid operation. You will work in a dynamic and multidisciplinary research environment and will be supervised by experienced researchers in power systems, optimization, and artificial intelligence. If you have a strong technical background, motivation to develop innovative solutions, and are goal-oriented, this is your opportunity to contribute to a stronger and more sustainable energy future. The duration of the internship is six months.

How you’ll make an impact

• Contribute to research activities on ML-based methods for power system monitoring
• Investigate, deploy and refine foundation models for representing power grid topology, measurements, and operating conditions
• Combine ML-driven methods with numerical optimization and power system physics
• Evaluate the proposed methods through simulation studies and benchmarking
• Report and disseminate results within the team, write technical documentation, and contribute creative ideas towards industrial implementation

Your background

• Enrolled in an MSc program in Electrical Engineering, Computer Science, Applied Mathematics, or a related field
• Strong background in numerical optimization. Power system knowledge is a plus
• Good knowledge of machine learning and deep learning. Exposure to graph neural networks, foundation model or machine learning adaptation strategies is a plus
• Experience in Python or C++ programming and MATLAB
• Experience with PyTorch or similar deep learning frameworks
• Excellent communication skills, team player attitude, initiative, and creativity
• Fluency in English, written and spoken

More about us

We are a technology-driven company with a strong focus on innovation, continuous improvement, and sustainable manufacturing. We offer flexible working conditions, dedicated mentorship, and a supportive, inclusive environment where you can grow personally and professionally – empowering you to thrive while balancing life and work.

Non-EU/EFTA citizens, please note that an official university certificate showing that an internship is a mandatory part of your studies is required.

Accessibility and reasonable accommodation

Qualified individuals with a disability may request a reasonable accommodation if you are unable or limited in your ability to use or access the Hitachi Energy career site as a result of your disability. You may request reasonable accommodations by completing a general inquiry form on our website.

This is solely for job seekers with disabilities requiring accessibility assistance or an accommodation in the job application process. Messages left for other purposes will not receive a response.

Use of Al and automated tools in recruitment

As part of our recruitment process, Hitachi Energy uses digital and automated tools, including Al-supported solutions, to assist with activities such as application screening, job matching, and interview scheduling. These tools are designed to support our recruiters and do not replace human decision-making. Candidate data is processed in accordance with applicable data protection and employment laws as well as Hitachi’s Global Data Privacy Notice.

Background Screening and Security Checks

As part of the hiring process, Hitachi Energy conducts pre-employment background checks that may include verification of employment history, education, criminal records, and other relevant information, in accordance with applicable laws.

For certain roles—particularly those involving access to sensitive information, financial responsibilities, client data, regulated environments, or security-sensitive functions—additional or more comprehensive background or security screenings may be required. These may include, but are not limited to, enhanced criminal history checks, credit history reviews (where legally permissible), sanctions screening, or other due diligence measures aligned with the responsibilities of the position.

The scope and depth of any background or security review will be determined based on the nature of the role and business necessity, and will always be conducted in compliance with applicable federal, state, and local laws. Candidates will be notified and, where required, asked to provide consent prior to the initiation of any such checks.