**Job Description**
This Ph.D. candidate position focuses on developing deep learning algorithms for real-time monitoring and anomaly detection within Norway’s future energy system, specifically utilizing data from Statnett’s “Digital Substation.” The project involves collaboration with Statnett, CERN, ETH Zürich, and the University of Oslo, aiming to improve the security and efficiency of power supply through advanced AI tools and efficient handling of big data with high time-series resolution. The candidate will work on online monitoring and anomaly detection tailored for this specific data, with planned research stays at collaborating institutions.
**Skills & Abilities**
• Strong academic background from previous studies
• Ability to work independently, in a structured way, set goals and make plans to achieve them
• Ability to present and discuss research with other professionals
• Curiosity and strong motivation for the subject
• Flexibility and openness to adjusting the plan for the project as needed
• Experience in research project works (Preferred)
• Good knowledge and experience in the use and development of machine learning algorithms (Preferred)
**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 compared to NTNU’s grading scale
• Meet requirements for admission to the Doctoral Programme at the Faculty of Engineering at NTNU
**Experience**
Other:
• Strong academic background from previous studies
• Experience in research project works (Preferred)
• Good knowledge and experience in the use and development of machine learning algorithms (Preferred)
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