Publisher
source

Norwegian Institute of Science and Technology

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PhD Candidate in Efficient Edge Intelligence Models at NTNU Norwegian University of Science and Technology in Norway

Degree Level

PhD

Field of study

Computer Science

Funding

PhD Candidate position at NTNU with a gross salary normally NOK 580,000 per annum depending on qualifications and seniority. The employment period is four years, with 25% devoted to career-enhancing work. The post is a paid employment position rather than a scholarship.

Deadline

Sep 23, 2026

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Country

Norway

University

Norwegian Institute of Science and Technology

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Keywords

Computer Science
Electrical Engineering
Information Technology
Deep Learning
Artificial Intelligence
Optimisation
Embedded System
Large Language Models
ML

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About this position

NTNU (Norwegian University of Science and Technology) is advertising a PhD Candidate in Efficient Edge Intelligence Models at the Department of Computer Science in Trondheim, Norway. The project sits at the intersection of deep learning, computer systems, edge intelligence, and efficient AI, with a focus on advancing models and methods for resource-constrained edge platforms.

The successful candidate will join an international and collaborative research environment and contribute to research on efficient AI systems. The post includes doctoral education, research publications, dissemination, participation in the system software group, and possible international activities such as conferences or research stays abroad.

Eligibility highlights: a relevant Master's degree in Computer Science or equivalent, including a substantial independent project (minimum 30 ECTS); strong academic performance (typically B or better on NTNU's scale); and English proficiency equivalent to IELTS 7 or TOEFL above 100. Preferred experience includes first-author publications in machine learning, embedded systems, or edge intelligence; hands-on work with Nvidia Jetson or similar edge platforms; and knowledge of deep learning optimization such as pruning and quantization, plus large language models or multimodal models.

Funding: this is a salaried PhD employment at NTNU, normally NOK 580,000 gross per year, with a four-year appointment and 25% of time allocated to career-enhancing work.

Application deadline: 23 September 2026. Applications must be submitted electronically via Jobbnorge.no and include transcripts, diplomas, CV, project outline, motivation letter, publications, English documentation, and three referees.

Funding details

PhD Candidate position at NTNU with a gross salary normally NOK 580,000 per annum depending on qualifications and seniority. The employment period is four years, with 25% devoted to career-enhancing work. The post is a paid employment position rather than a scholarship.

What's required

Applicants must meet admission requirements for the faculty's Doctoral Programme. A relevant Master's degree in Computer Science or equivalent is required, including a major independent project of at least 30 ECTS equivalent to a master's thesis. Candidates should have a strong academic background with an average grade of B or better on NTNU's scale, or an equally strong foundation if grades are not letter-based; exceptionally suitable applicants with relevant work experience and/or peer-reviewed publications may be considered. English proficiency equivalent to IELTS 7 or TOEFL above 100 is required. Preferred qualifications include first-author publication in machine learning, embedded systems, or edge intelligence; hands-on experience with Nvidia Jetson or other edge platforms; strong knowledge of deep learning, especially large language models or multimodal models; and experience with pruning and quantization.

How to apply

Apply electronically via Jobbnorge.no before the deadline. Include transcripts and diplomas for Bachelor's and Master's degrees, CV, a project outline, a short motivation letter, publications and other relevant research work, documentation of English proficiency, and contact information for three referees. If applicable, also attach documentation of foreign education and diploma supplements.

More information can be found here

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