Phd Candidate in Deep Learning for Real-Time Monitoring of the future Norwegian Energy System

**Job Description**
This Ph.D. position focuses on developing advanced deep learning algorithms for real-time monitoring and anomaly detection within the future Norwegian power system. The project, in collaboration with Statnett, CERN, ETH Zürich, and the University of Oslo, will leverage data from Statnett’s “Digital Substation” to enhance secure power supply operations through efficient AI tools and big data handling with high time-series resolution. The candidate will contribute to Norway’s climate objectives by facilitating the integration of more solar and wind production sources.

**Skills & Abilities**
• Ability to work independently, in a structured way, set goals and make plans to achieve them
• Proficiency in presenting and discussing research with other professionals
• Curiosity and a strong motivation for the subject
• Flexibility and openness to adjusting the plan for the project as needed
• Experience in research project works (advantage)
• Good knowledge and experience in the use and development of machine learning algorithms (advantage)
• Scientific publications (advantage)

**Qualifications**
Required Degree(s) in:
• Computer Science
• Applied Mathematics
• Physics
• Electrical Engineering
• Related field

Other:
• Master’s degree or equivalent (corresponding to a five-year Norwegian course with 120 credits at master’s level)
• Average grade from Master’s degree study equal to B or better (NTNU’s grading scale)
• Admission to the Doctoral Programme at the Faculty of Engineering at NTNU within three months of employment start date

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