PhD Candidate in Multimarket Bidding Decision Support in Nordic Power Markets

Arbeidsplassen; Trondheim; On-site; NOK 522,000 - 638,000; Full time

Benefits offered by this job

International environment

Friday coffee

Norwegian language training

Job summary

NTNU is inviting applications for a PhD Candidate in Multimarket Bidding Decision Support in Nordic Power Markets. You will work within aiD, contributing to trustworthy AI-supported methods for multimarket bidding and decision support, coordinating day-ahead and mFRR markets with uncertain renewable generation.

The role emphasizes learning-based and optimization-based methods, with a focus on knowledge embedding and risk-aware decisions.

Qualifications

• Master's degree completed before autumn 2026.
• Strong mathematical and quantitative skills with good programming ability.
• English language skills at CEFR B2 level or higher.

Responsibilities

• Carry out high-quality research within the described framework.
• Participate in activities of the EMESP research group.
• Complete academic training of at least 30 ECTS.
• Contribute to publications in relevant journals and to science dissemination.
• Participate in international activities such as conferences or research stays.

Skills

Julia

Python

English proficiency

Quantitative skills

Education

Master's degree in Electrical Power Engineering or related field

Tools

Julia

Python

Job description

PhD Candidate in Multimarket Bidding Decision Support in Nordic Power Markets

NTNU - Norwegian University of Science and Technology

Stillingstittel PhD Candidate in Multimarket Bidding Decision Support in Nordic Power Markets

NTNU is a broad-based university with atechnical-scientific profile and a focusin professional education. The university is located in three cities with headquarters in Trondheim.

At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world.

You will find more information about working at NTNU and the application process here.

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Are you motivated to take a step towards a doctorate and open up exciting career opportunities? Do you have a background in electrical power engineering, operations research, or a related field, and are you interested in energy systems and markets?As a PhD candidate with us, you will work to achieve your doctorate, and at the same time gain valuable experience that qualifies you for a further career in higher education and research, both in and outside academia.

Our work environment is defined by its friendly and supportive atmosphere, with regular gatherings such as professional meetings within the research group, weekly colloquia, shared lunches, and “Friday coffee” sessions to end the week. These formal and informal events offer opportunities to share ideas, celebrate milestones, and build relationships. PhD candidates also organize social activities open to everyone interested, fostering a welcoming and inclusive community.

Your immediate Line Manager will be the Head of Department.

About the project

The position will be part of aiD,the Norwegian Centre on AI for Decisions , an interdisciplinary national AI center led by NTNU and SINTEF. AID brings together academic institutions, research organizations, and more than 50 professional organizations. Its primary objective is to advance AI for decision-making through fundamental research and real-world use cases, ensuring that AI-enhanced human decisions and autonomous systems are effective, safe, and trustworthy in sectors critical to society.

This PhD project will contribute to aiD by developing trustworthy AI-supported methods for multimarket bidding and decision support in Nordic power markets. The rapid integration of wind power, battery storage, and other flexible resources is creating new opportunities for market participation, but also more complex decision-making problems. Energy producers increasingly need to coordinate decisions across day-ahead, balancing, and other electricity markets while dealing with uncertain renewable generation, activation needs, regulation and imbalance prices, and rapidly changing market conditions. Recent developments such as 15-minute market time units, automated mFRR energy activation, and flow-based market coupling further increase the need for decision-support methods that are fast, robust, risk-aware, and suitable for real-time operation.

The project will focus on how AI and mathematical optimization can be combined to support sequential bidding decisions under uncertainty. The initial use case will consider a wind power operator with battery storage participating in the day-ahead market and the mFRR capacity and energy activation markets. The research will investigate how probabilistic forecasts, market-state and regime information, and the future value of battery flexibility can be incorporated into bidding decisions. A central scientific question will be to determine which parts of the decision problem are best handled by data-driven learning and which should remain within structured optimization. In line with AID’s research areas, the project will emphasize knowledge embedding, uncertainty representation, risk-aware decision-making, computational efficiency, generalization under changing market conditions, and safe constraint handling.

The PhD candidate will develop and validate decision-support methods based on deep reinforcement learning, stochastic optimization, and hybrid combinations of learning and optimization. Learning-based policies will be compared with equivalent rolling stochastic optimization benchmarks operating with the same information and operational constraints. The project will also explore how AI can be used to approximate, accelerate, contextualize, or enhance optimization, for example by learning future flexibility value, selecting relevant uncertainty scenarios, or reducing computational complexity. The methods will initially be tested for coordinated day-ahead and mFRR market participation and may later be extended to more strongly coupled market combinations and other flexible energy resources. The project therefore offers the opportunity to work at the intersection of artificial intelligence, optimization, electricity markets, and renewable energy systems, while addressing the growing need for trustworthy and computationally practical AI-supported decision making in future power markets.

Duties of the position

• Carry out research of high quality within the framework described above
• Participate in activities of theEMESP research group
• Complete academic training consisting of coursework corresponding to a minimum 30 ECTS
• Contribute to publications in relevant journals and to popular science dissemination
• Participate in international activities such as conferences and/or research stays at foreign educational institutions

Career-enhancing work, which is in addition to the research project and doctoral education, may be offered to a candidate who demonstrates clear motivation and ability for such work, and if the Department determines there is a need. Examples of career-enhancing work include, but are not limited to, contributing to teaching, laboratory and exercise teaching, supervision, and examination work within the employee's areas of competence.

Be prepared for changes to your work duties after employment.

Required selection criteria

• You must have a relevant Master's degree in either electrical power engineering, control engineering, managerial economics with strong quantitative skills, or physics or mathematics with a specialization in operations research. Your course of study must correspond to a five-year Norwegian course, where 120 credits have been obtained at master's level. Master's students can apply, but the master's degree must be obtained and documented before starting the position and no later than autumn 2026.
• You must have a strong academic background from your previous studies and have an average grade from your Master's degree study, or equivalent education, which is equal to B or better compared toNTNU's grading scale . If you do not have letter grades from previous studies, you must have an equally good academic foundation. If you have a weaker grade background, you may be considered if you can document that you are particularly suitable for a PhD education, i.e., by having relevant work experience and/or published scientific papers.
• You must have English language skills, both written and spoken, corresponding to the scaleB2 in the Common European Framework of Reference for Languages (CEFR).Applicants who are not native English speakers are encouraged to document their English language proficiency. This can be done through an approved English language test. One of the following test scores could be documented for this purpose:
  • TOEFL internet-based test (iBT) - Score equivalent to the B2 level: 79 - 101.
  • IELTS - Score equivalent to the B2 level: 5.5 - 6.0
  • Cambridge English - Score equivalent to the B2 level: 160 - 179.

Further assessment of both written and oral English language skills, as well as the ability to communicate fluently, will be conducted throughout the selection process and during any interviews for all applicants.

• Work and/or research experience in electricity and power markets, imbalance forecasting, reinforcement learning, and operations research or optimization.
• Excellent programming and modeling skills, preferably in Julia, Python, or a similar programming language.
• English language skills, both written and spoken, corresponding to the scaleC1 in the Common European Framework of Reference for Languages (CEFR). See which scores are equivalent to the C1 levelhere .

Personal characteristics

To complete a doctoral degree (PhD), the candidate is expected to:

• demonstrate strong motivation, curiosity, and a learning-oriented mindset
• work independently, take initiative, and maintain good structure and discipline in their work
• communicate effectively and collaborate well with supervisors and peers
• show resilience and work constructively when facing challenges or setbacks
• demonstrate integrity and a strong sense of responsibility in their research conduct

Emphasis will be placed on personal and interpersonal qualities.

We offer

• An exciting job with an importantmission in society
• Developing tasks in a strong and international professional environment
• Open and inclusive working environment with committed colleagues
• Social activities organized by PhD Students
• Weekly social gathering on Fridays (Friday coffee)
• Free Norwegian language training at a basic level (A2)

We strive to attract employees with different skills, life experiences and perspectives to contribute to even better problem solving of our societal mission in research and education.

If you think this position is relevant and interesting, we encourage you to apply, regardless of gender, functional ability, and cultural background, or whether you have been out of work for a period of time.

At NTNU we want to increase the proportion of women in scientific positions. We have a number ofmeasures to promote equality.

Salary and conditions

In the position of PhD Candidate, code 1017, your gross salary will normally be NOK 580 000,-per annum depending on qualifications and seniority. A 2% statutory contribution to the State Pension Fund is deducted from the salary.

The employment period is 3 years, with the possibility of an additional 3 to 12 months of employment related to career-enhancing activities.

The option for career-enhancing work may be offered to a candidate who has clear motivation and ability for such work, and if the Department deems it necessary. This will be clarified with the candidate during and after any interview.

For employment as a PhD Candidate, it is a prerequisite that you gain admission to the PhD programme inElectric Power Engineering within three months of your employment contract start date, and that you participate in an organized doctoral programme throughout the period of employment.

The position is conditional on external funding.

As an employee at NTNU, it is important that you keep yourself up to date with academic and organizational changes and adapt to them.

For the necessary professional and social interaction, it is a prerequisite that you are physically present and available to the institution on a daily basis.

The attachments (including a description of your scientific work) must accompany the application as these documents form the basis of the application assessment. The documents must be in Norwegian/a Scandinavian language or English.

When assessing the best qualified, we emphasize necessary qualifications such as education, experience and personal suitability. Motivation for the position, ambitions, and potential for research will also count when assessing the candidates. NTNU recognizes a wide range of academic contributions and has committed itself to The San Francisco Declaration on Research Assessment and CoARA (responsible assessment of research and recognition of a greater breadth of academic contributions in accordance with NTNU's social mission).

General information

A public list of applicants with name, age, job title and municipality of residence is prepared after the application deadline. If you wish to be exempt from entry on the public applicant list, this must be justified. Assessment will be made in accordance withcurrent legislation . You will be notified if the exemption is not granted.

If you have any questions about the position, please contact Associate Professor Jayaprakash Rajasekharan by email [e-mail] .

If you have any questions about the recruitment process, please contact Head of Office Bodil Wold by email at [e-mail]

The city of Trondheim is a modern European city with a rich cultural scene.Trondheim is the tech capital of Norway with a population of 200,000.The Norwegian welfare state, including healthcare, schools, kindergartens and overall equality, is probably the best of its kind in the world. Professional subsidized day-care for children is easily available. Furthermore, Trondheim offers great opportunities for education (including international schools) and possibilities to enjoy nature, culture and family life and has low crime rates and clean air quality.

Om bedriften

NTNU - knowledge for a better world

The Norwegian University of Science and Technology (NTNU) creates knowledge for a better world and solutions that can change everyday life.

Department of Electric Energy

The Department of Electric Energyis one of the seven departments at the Faculty of Information Technology and Electrical Engineering. Our department is Norway’s leading in the field, and our vision is to be at the centre of the digital, green shift. We have excellent collaboration with business and industry as well as other universities and research organizations internationally. This gives us outstanding opportunities for interdisciplinary research with high relevance for the society, addressing industrial needs and global challenges.