Software Developer / Software Developeress

ETH Zürich - September 10, 2025

Research Center for Energy Networks

The Research Center for Energy Networks (Forschungsstelle Energienetze – FEN) at the Swiss Federal Institute of Technology, Zurich (ETHZ), serves as a vital connection among academic research, industry, society, and policy makers in the energy sector. Our mission is to facilitate the transition to a more sustainable, reliable, and cost-effective future energy system by delivering technology-neutral, independent quantitative analysis to utilities, grid operators, industrial associations, and federal institutions.

FEN's research leverages extensive datasets and advanced modeling techniques to evaluate and optimize energy systems. We have developed proprietary tools and utilize open-source datasets to support our research activities across various temporal, spatial, and energy domains. Aiming to enhance our capabilities, we seek to integrate our modeling chain into a cohesive framework while unifying our datasets into a state-of-the-art data structure that enables seamless interoperability and sophisticated analytics.

Position Overview

We are in search of an experienced Software Developer with data science expertise to take on a crucial role in the design and implementation of a consistent framework that integrates our existing in-house tools and necessary datasets. The ideal candidate will develop a unified data structure that effectively manages, processes, and provides access to diverse datasets pertinent to energy systems and electricity grids. This role will ensure the scalability, interoperability, and robustness of the framework for various analytical purposes.

As part of this role, you will work closely with researchers and domain experts to gather requirements and translate them into efficient software solutions. You will also be responsible for maintaining and improving data pipelines, as well as contributing to the long-term development of our research infrastructure. A key aspect of this position will involve setting up a reliable version control system and implementing industry-standard software development practices for our in-house tools.

Qualifications

  • Education: Master’s or PhD in Computer Science, Data Science, Software Engineering, or a related field.
  • Experience: Proven track record in data engineering, software development, and integration of complex tools or systems.
  • Technical Skills:
    • Excellent programming skills (e.g., Python, C++, or similar).
    • Experience with data management, database systems, and API development.
    • Knowledge of software architecture, modular frameworks, and version control systems (e.g., Git).
    • Familiarity with energy systems modeling or related domains is an advantage.
  • Soft Skills:
    • Outstanding analytical and problem-solving abilities.
    • Strong communication skills and ability to collaborate in an interdisciplinary team.
    • Self-motivated, organized, and capable of driving projects independently.

Working Environment

  • Collaborate as a member of a highly motivated team of scientists.
  • Engage in an international environment alongside established experts.
  • Contribute to the Swiss energy transition.
  • Opportunity to publish scientific work.

Apply online using the form below. Please note that only applications matching the job profile will be considered.

Additional Information

For more details about the Research Center for Energy Networks, please visit our website. If you have any questions regarding the position, feel free to contact Dr. Turhan Demiray, the Director of the Research Center for Energy Networks (FEN), via e-mail: demirayt@ethz.ch (no applications).

Please note that pre-selection is conducted by the responsible recruiters, not by artificial intelligence.

The GTC of ETH Zurich apply for recruitment services.

Location : Zürich ETH-Zentrum
Country : Switzerland

Application Form

Please enter your information in the following form and attach your resume (CV)

Only pdf, Word, or OpenOffice file. Maximum file size: 3 MB.