PhD Candidate in Machine Learning & Signal Processing for Industrial Applications

**Job Description**
The Department of Electronic Systems at NTNU is seeking a Ph.D. Candidate for a research fellowship in Machine Learning & Signal Processing for Industrial Applications. This position is linked to the LeDAS project, funded by the Research Council of Norway, and involves collaboration with several partners including NORCE, SINTEF, UiB, Equinor, and Aker BP. The project’s main objectives include developing and integrating signal processing and machine learning methodologies to interpret distributed acoustic sensing (DAS) data from production wells, focusing on virtual flow metering and well inflow applications. The research tasks will involve feature identification and selection for robust and trustworthy models. The successful candidate will work to achieve their doctorate, gaining valuable experience for a career in academia and beyond.

**Skills & Abilities**
• Good oral and written presentation skills in English (equivalent to C1 level)
• Strong mathematical background
• Research-oriented master thesis in a related field (e.g., signal processing, statistical machine learning, applied mathematics)
• Significant experience with programming in Python
• Ability to work in a structured way, set goals, and make plans
• Ability to present and discuss research with other professionals
• Ability to get involved and contribute constructively with feedback
• Ability to work constructively under pressure or in the face of adversity
• Curiosity and a strong motivation for the subject
• (Preferred) Experience in process monitoring
• (Preferred) Publication activity in relevant disciplines
• (Preferred) Good oral and written presentation skills in Norwegian/Scandinavian (equivalent to B1 level)

**Qualifications**
Required Degree(s) in:
• Electrical Engineering
• Computer Science
• Applied Mathematics
• Equivalent relevant disciplines

**Experience**
Other:
• Master’s degree (corresponding to a five-year Norwegian course with 120 credits at master’s level)
• Average grade from Master’s degree study (or equivalent) equal to B or better based on NTNU’s grading scale
• Meeting requirements for admission to the PhD Program in Electronics and Telecommunication
• Research-oriented master thesis in a related field (e.g., signal processing, statistical machine learning, applied mathematics)
• Significant experience with programming in Python
• (Preferred) Experience in process monitoring
• (Preferred) Publication activity in relevant disciplines

Note: We’ve analyzed the actual job post using AI, for more details visit the original job post by clicking on “Apply Now”!