PhD Candidate in AI-Supported Long-Term Hydropower Scheduling

Ntnu; Trondheim; Hybrid; NOK 522,000 - 638,000; Full time

Benefits offered by this job

Open and inclusive working environment

Free Norwegian language training (A2)

Job summary

NTNU seeks a PhD Candidate in AI-Supported Long-Term Hydropower Scheduling to join the Electricity Markets and Energy Systems Planning group. The candidate will pursue doctoral studies while developing AI-enhanced optimization for hydro resources, reservoirs, and energy markets in a Nordic context.

The project is hosted within AID, a national AI centre led by NTNU and SINTEF, emphasizing trust and decision-support in power systems. Supervisors include several renowned experts in the field.

Qualifications

• Master's degree completed by autumn 2026 or earlier with strong quantitative background.
• Excellent academic record with a solid foundation for PhD study.
• Experience with optimization modeling and solver tools is valued.
• Proficiency in English at B2 level or higher.

Responsibilities

• Conduct high-quality research within the project framework.
• Participate in EMESP group activities and training.
• Complete coursework equivalent to at least 30 ECTS.
• Contribute to publications and scientific dissemination.
• Engage in international conferences or research stays.

Skills

Optimization modelling

Numerical optimization

English (B2)

Research mindset

Education

Master's degree in electrical power engineering / CS / control engineering / physics / maths with OR

Tools

Julia

Python

JuMP

Pyomo

Gurobi

CPLEX

HiGHS

Job description

The Department of Electric Energy has a vacancy for a

PhD Candidate in AI-Supported Long-Term Hydropower Scheduling

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.

About the position

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 centre 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 long-term hydropower scheduling. Hydropower plays a central role in the Nordic power system, and deciding when to use or store water is becoming increasingly important as the energy system faces more uncertainty from weather, renewable generation, market developments, and future electricity demand. These decisions depend on uncertain inflows, future electricity prices, reservoir levels, cascade constraints, and the nonlinear relationship between water release and electricity production. Improving such decisions is essential for efficient renewable energy use, energy security, and the reliable operation of hydro-dominated power systems.

The project will focus on how AI can support advanced optimization models for hydropower and energy-system planning. In particular, the research will investigate how the future value of stored water can be represented more accurately when hydropower production is nonlinear and when short-term operational conditions influence long-term reservoir decisions. In line with AID’s research areas, the project will emphasize trust, knowledge embedding, generalization under uncertainty, and human-interpretable decision support.

The PhD candidate will develop and validate a hybrid methodology that combines established stochastic optimization with AI-based learning. The aim is not only to develop new algorithms, but also to understand how AI can be used safely and reliably in decision-support tools for the energy sector. The enhanced framework will be tested on Nordic hydropower use cases, including long-term and medium-term hydropower scheduling, multi-reservoir cascade operation, hydropower participation in energy and reserve markets, and planning under high renewable variability. In this way, the project responds to the growing need for safe and trustworthy AI tools in demanding, decision-critical systems.

The PhD candidate will be hosted in the Electricity Markets and Energy Systems Planning (EMESP) group at the Department of Electric Energy, NTNU. The main supervisor will be Professor Hossein Farahmand, with co-supervision from experts in stochastic hydropower optimization and AI for decision-making, including Professor Arild Helseth, Associate Professor Jayaprakash Rajasekharan, Professor Sebastien Gros, and Research Manager Signe Riemer-Sørensen, depending on the final methodological focus of the PhD project.

Duties of the position

• Carry out research of high quality within the framework described above
• Participate in activities of the EMESP 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, computer science, control engineering, chemistry, 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 to NTNU'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/publishable scientific papers.
• Experience with optimization modelling and numerical optimization tools, such as JuMP, Pyomo, Gurobi, CPLEX, HiGHS, or similar frameworks and solvers, will be considered an important qualification.
• You must have English language skills, both written and spoken, corresponding to the scale B2 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 markets, hydropower scheduling, energy system modeling, and operations research or optimization.
• Very good programming and modeling skills, preferably in Julia, Python, or a similar programming language.
• Knowledge and/or experience with Machine Learning, Reinforcement Learning, AI-based time-series forecasting
• English language skills, both written and spoken, corresponding to the scale C1 in the Common European Framework of Reference for Languages (CEFR). See which scores are equivalent to the C1 level here .

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

Evaluate and remove/add what is relevant for the position.

• An exciting job with an important mission in society
• Developing tasks in a strong and international professional environment
• Open and inclusive working environment with committed colleagues
• 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.

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

If you cannot document skills in Norwegian, Swedish, or Danish at level A2 upon employment, NTNU offers the opportunity to take Norwegian courses corresponding to at least 15 credits. NTNU will facilitate this.

For employment as a PhD Candidate, it is a prerequisite that you gain admission to the PhD programme in Electric 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.

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 with current legislation . You will be notified if the exemption is not granted.

If you have any questions about the recruitment process, please contact the 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.

NTNU - knowledge for a better world

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 organisations internationally. This gives us outstanding opportunities for interdisciplinary research with high relevance for the society, addressing industrial needs and global challenges.