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Thomas Øyvang

6 months ago

PhD in Real-time Predictive Fleet Modelling and Optimization for Coordinated Reactive Power Control University of South-Eastern Norway in Norway

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Expired

Country flag

Country

Norway

University

University of South-Eastern Norway

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Keywords

Computer Science
Machine Learning
Electrical Engineering
Mathematics
Wind Energy
Solar Technology
Reinforcement Learning
Digital Twin Technology
Optimisation
Energy Security
Power System
Control System
Physics

About this position

The University of South-Eastern Norway (USN) invites applications for a PhD research fellowship in Real-time Predictive Fleet Modelling and Optimization for Coordinated Reactive Power Control. This position is part of the CoordQ project, which aims to enhance reactive power and voltage coordination in the Nordic Power System, funded by the Research Council of Norway. The successful candidate will join the Department of Electrical Engineering, IT and Cybernetics at the Faculty of Technology, Natural Sciences and Maritime Sciences, working closely with leading research and industry partners including NTNU, Statnett, Statkraft, Skagerak Kraft, Lede, and Aker Solutions.

The doctoral project focuses on developing real-time predictive fleet modelling and optimization methods for reactive power dispatch, integrating co-optimization strategies assisted by machine learning. The research will address both dispatchable resources (such as hydro power) and non-dispatchable resources (such as offshore wind and solar power), aiming to reduce power system losses, improve coordination, and stabilize grid operations. Specific objectives include creating digital twin models for synchronous generators, implementing co-optimization methodologies across multiple time scales, designing optimal control strategies for reactive power production and absorption, and integrating advanced machine learning techniques like reinforcement learning and graph neural networks. Validation will involve real-world and stochastic operational scenarios, including extreme events.

The PhD position is for a fixed term of three years, with pure organized research training. The candidate will be expected to complete the doctoral programme, produce scholarly publications, actively participate in the CoordQ project, and engage with the Electrical Power Systems research group. Opportunities for collaboration and research stays with national and international partners are available. The place of work is campus Porsgrunn, and it is required that the candidate resides nearby to participate fully in the academic environment.

Applicants must hold a master’s degree (120 ECTS credits) or equivalent in relevant STEM fields such as electrical power engineering, control system engineering, physics, environmental engineering, mathematics (operations research), computer science, or machine learning. A weighted average grade of B or higher is required, and applicants in their final semester may apply. Excellent written and oral English skills are mandatory, with international applicants required to provide valid English proficiency certificates unless exempt. Admission to USN’s doctoral programme in Technology must be secured within three months of starting. Security clearance and a background check are required prior to employment.

The position offers a salary in accordance with the Norwegian State salary scale for PhD research fellows (NOK 550,800 per year), membership in the Norwegian Public Service Pension Fund, and favorable pension, insurance, and loan schemes. The working environment is inclusive and diverse, with career advice and guidance throughout the doctoral programme. Norwegian language courses are available for international candidates.

To apply, submit your application electronically via the Jobbnorge portal by the deadline (28 May 2026). Required documents include a cover letter, detailed CV, certified diplomas and transcripts, a 2–4 page project proposal, documentation of English proficiency, and contact information for references. All documents must be in English or a Scandinavian language. Applications exceeding 30 MB must be compressed. For further information, contact Associate Professor Thomas Øyvang ([email protected]).

USN is committed to diversity and encourages applications from all qualified candidates, including women, individuals with disabilities, and those with gaps in their CV or an immigrant background. The university offers a vibrant academic community, opportunities for professional development, and a meaningful role in addressing societal challenges through education and research.

Funding details

Available

What's required

Applicants must hold a master’s degree (120 ECTS credits) or equivalent in STEM fields such as electrical power engineering, control system engineering, physics, environmental engineering, mathematics (operations research), computer science, or machine learning. Documented knowledge of relevant quantitative and/or qualitative methodologies at master’s level is required. Weighted average grade of B or higher on the master’s degree and thesis. Degree must be completed by the start date; applicants in their final semester may apply. Excellent written and oral English skills are required. International applicants must provide valid English proficiency certificates (TOEFL, IELTS, CAE/CPE, PTE Academic) unless exempt by prior study or degree in English. Must meet formal requirements for admission to USN’s doctoral programme in Technology within three months of starting. Security clearance and background check required. Personal qualities include motivation, independence, teamwork, interdisciplinary interest, dissemination skills, resilience, analytical ability, flexibility, structured work habits, and constructive feedback.

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Professors

Associate Professor at University of South-Eastern Norway

University Name
Country flag

Norway

Research Interests

Power System

Energy Engineering

Power And Energy Systems

Distributed Generation

Power Systems