PhD Candidate: AI‑Driven Power Markets & Optimization

Norwegian University of Science and Technology (NTNU); Trondheim; On-site; NOK 522,000 - 638,000; Full time

Benefits offered by this job

Mentor program

Friday coffee

International environment

Career guidance

Job summary

NTNU’s Department of Electric Energy (IEL) seeks a highly motivated PhD candidate for a 3-year full-time position as part of the aiD project. The research focuses on AI-enabled decision support and multimarket bidding in Nordic power markets.

The PhD will work within the EMESP group, developing learning and optimization methods, and contribute to publications while completing required coursework. The role offers a collaborative, inclusive environment with weekly colloquia and social activities.

Qualifications

• Master’s degree in electrical power engineering, control engineering, managerial economics with strong quantitative skills, or physics/mathematics with operations research specialization.
• English language skills at CEFR B2 level (written and spoken).
• Admission to NTNU's Doctoral Programme within the stated timeframe (autumn 2026).

Responsibilities

• 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.

Skills

English proficiency

Programming skills

Education

Master’s degree (Electrical Power Eng/Control Eng/Operations Research/Physics/Math)

Tools

Julia

Python

Job description

NTNU’s Department of Electric Energy (IEL) seeks a highly motivated PhD candidate for a 3-year full-time position as part of the aiD project. The research focuses on AI-enabled decision support and multimarket bidding in Nordic power markets.

The PhD will work within the EMESP group, developing learning and optimization methods, and contribute to publications while completing required coursework. The role offers a collaborative, inclusive environment with weekly colloquia and social activities.