Norwegian Institute of Science and Technology
2 weeks ago
PhD Candidate in Machine Learning & Signal Processing for Industrial Applications Norwegian University of Science and Technology in Norway
Degree Level
PhD
Field of study
Computer Science
Funding
3-year PhD position, or 4-year position with 25% work assignments for the department. Salary is normally NOK 550,800 per year before deductions, depending on qualifications and seniority. The position is conditional on external funding.
Deadline
Oct 1, 2026
Country
Norway
University
Norwegian Institute of Science and Technology

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About this position
NTNU (Norwegian University of Science and Technology) is advertising a PhD Candidate in Machine Learning & Signal Processing for Industrial Applications in the Department of Electronic Systems. The position is based in Trondheim, Norway, and is linked to the LAIFA project (Leveraging AI in Flow Assurance), funded by the Research Council of Norway in collaboration with SINTEF, Equinor, and Total.
The research focus is on developing and integrating signal processing and machine learning methods to improve flow assurance using field data for safe and efficient petroleum production. The project specifically mentions reconstructing flow over space and time under different operating conditions, with research directions including physics-informed neural networks and transfer learning. The successful candidate will join the Signal Processing research group and may also be affiliated with BRU21, IoT@NTNU, and the Norwegian Open AI Lab.
This is a PhD opening (not a postdoc or master's call). The appointment is normally for 3 years, or 4 years with 25% work assignments. The salary is stated as NOK 550,800 per year before deductions, depending on qualifications and seniority. The position is conditional on external funding.
Eligibility highlights include a relevant Master's degree in Electrical Engineering, Computer Science, Applied Mathematics, or another relevant discipline; a strong academic record; admission eligibility for NTNU's Doctoral Programme in Electronics and Telecommunication; strong mathematical background; a research-oriented master's thesis in a related area; and significant programming experience, preferably Python. Good English communication skills are required, with TOEFL, IELTS, Cambridge CAE, or CPE accepted as documentation. Norwegian language skills are listed as preferred.
To apply, submit the application electronically via Jobbnorge.no with the required attachments: a short application letter, CV, transcripts and diplomas, a copy or draft of the master's thesis, a brief research vision, any publications or relevant research work, and contact information for two referees. The deadline is 2026-10-01.
Funding details
3-year PhD position, or 4-year position with 25% work assignments for the department. Salary is normally NOK 550,800 per year before deductions, depending on qualifications and seniority. The position is conditional on external funding.
What's required
Relevant Master's degree in Electrical Engineering, Computer Science, Applied Mathematics, or another relevant discipline; the degree must correspond to a five-year Norwegian course with 120 credits at master's level. Applicants must have a strong academic background, an average grade of B or better on NTNU's scale or equivalent, and meet admission requirements for the Doctoral Programme in Electronics and Telecommunication. Strong mathematical background and a research-oriented master's thesis in a related field such as signal processing, statistical machine learning, or applied mathematics are required. Significant programming experience, preferably in Python, and good oral and written English are required; TOEFL, IELTS, Cambridge CAE, or CPE can document English proficiency. Norwegian language skills are preferred.
How to apply
Apply electronically via Jobbnorge.no and include the required attachments: application letter, CV, transcripts and diplomas, master's thesis, research vision, publications if any, and two referees. Ensure the application clearly shows how your background matches the criteria. Submit before the deadline.
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