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Industrial postdoctoral researcher in Coordinated Security Analysis

Job in Location, Tucker County, West Virginia, USA
Listing for: Nordic RCC
Full Time position
Listed on 2026-05-16
Job specializations:
  • Research/Development
    Research Scientist
Salary/Wage Range or Industry Benchmark: 70000 - 90000 USD Yearly USD 70000.00 90000.00 YEAR
Job Description & How to Apply Below
Location: Location

Industrial postdoctoral researcher in Coordinated Security Analysis

If you are passionate about applied research and want to contribute towards a more sustainable, resilient and cost-efficient power system, you have come to the right place. This position will give you an unprecedented opportunity to side with Nordic TSOs and key European stakeholders for unlocking the true potential of numerical optimization and artificial intelligence in real operational scenarios.

Nordic RCC – supporting security of supply and the green energy transition

The Nordic Regional Coordination Centre (RCC) provides critical services and insights to support the national Transmission System Operators (TSOs) in Finland, Norway, Sweden and Denmark — to ensure the efficient operation and use of the Nordic power system and high security of power supply at any time. Based in Copenhagen, Nordic RCC is one of six RCCs in Europe, equally owned by the Nordic region's four electricity TSOs:
Fingrid, Statnett, Svenska Kraftnät, and Energinet.

As European power systems integrate and evolve to meet climate goals, Nordic RCC provides regional coordination, integrated services, regional insights and recommendations to the Nordic TSOs and their control centres, to support cross-border operational security 24/7.

We are seeking a highly motivated industrial Postdoctoral researcher to join a newly established research project funded by Innovation Fund Denmark in close collaboration with the Danish Transmission System Operator, the Technical University of Denmark and Nordic RCC.

From this position, you will have the opportunity to address one of the core challenges of modern power system operation: how to preserve physical realism, security guarantees and cost effectiveness while achieving computational tractability at system scale. You will play a key role in strengthening the development of scalable, physics-aware surrogate models enabling Remedial Action Optimization (RAO) and Coordinated Security Analysis (CSA) for large-scale power systems in different time horizons.

As you take part in one of the work packages of the Nordic-Sec project, your focus will be on:

  • Learning about Remedial Action Optimization and Coordinated Security Analysis as the foundation for your applied research.
  • Developing analytical, reduced-order, and ML-based surrogate models to find optimal sets of remedial actions under real operational conditions.
  • Maintaining and documenting an open repository in collaboration with project partners.
  • Authoring high-impact publications on physics-aware ML and scalable optimization.
  • Mentoring MSc and PhD students and contributing to project dissemination.

You will be working side by side with power system engineers, data scientists and software developers delivering production-grade applications. In addition, you will have a direct link with DTU to learn about state-of-the art solutions together with other researchers in the project.

This unique combination of industry and research perspectives places you in a central scientific role in a high-impact Nordic research project with advisory from key European stakeholders, access to real operational data, strong collaboration with Nordic TSOs and the possibility to visit their offices for short external stays.

Requirements

Due to the nature of this position as industrial Postdoctoral researcher, some qualifications are required since you’ll need them from the get-go:

  • A PhD degree in power systems engineering or a closely related field.
  • Strong expertise in applied numerical optimization and/or AI techniques paired with advanced modelling, data‑driven methods, and/or surrogate modelling.
  • Ability to develop well‑structured, readable, and maintainable research code in Python or other programming languages supporting data analysis and visualization for large datasets.
  • Experience with collaborative code development using Git‑based version control (e.g. Git Hub or Git Lab), including branching, pull requests, and code review workflows.
  • Full professional proficiency in spoken and written English paired with excellent communication skills.

The list of the following research areas can provide you an…

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