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Kimmo Kansanen

Professor at Norwegian University of Science and Technology

Norwegian Institute of Science and Technology

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Norway

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Research Interests

Artificial Intelligence

20%

Data Science

20%

Networking

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Signal Processing

20%

Computer Science

20%

Mathematics

20%

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Positions2

Publisher
source

Kimmo Kansanen

University Name
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Norwegian University of Science and Technology

PhD Candidate in Distributed Machine Learning at NTNU

The Department of Electronic Systems at the Norwegian University of Science and Technology (NTNU) invites applications for a PhD Candidate in Distributed Machine Learning. NTNU is Norway’s leading technical-scientific university, with a strong focus on professional education and research excellence. The university is headquartered in Trondheim and is home to 9,000 employees and 43,000 students, all working towards creating knowledge for a better world. This PhD position is part of the SURE-AI national AI centre, a major initiative funded by the Research Council of Norway (2025-2030) to advance artificial intelligence research and innovation. SURE-AI aims to develop new algorithms for inference and decision-making, focusing on efficiency, transparency, and ethical alignment. The centre brings together 19 Norwegian partners and researchers from 15 international institutions, fostering interdisciplinary collaboration across academia, industry, and the public sector. More information about SURE-AI can be found at sure-ai.no . The research will focus on distributed machine learning, leveraging communication and distributed computing to utilize distributed datasets and computational resources. The project addresses challenges such as network outages and computational bottlenecks, aiming to make distributed machine learning robust and scalable. The successful candidate will participate in SURE-AI project activities, contribute to academic publications and popular science dissemination, and engage with the signal processing group at NTNU. International activities, such as conferences and research stays, are encouraged. Applicants must hold a relevant Master's degree in electronics, mathematics, data science, communication technology, or equivalent, corresponding to a five-year Norwegian course with 120 credits at master's level. Master students may apply if the degree is completed before starting the position and no later than 30.10.2026. A strong mathematical background and a research-oriented master thesis are required. Candidates should have an average grade of B or better on the NTNU grading scale, or equivalent. Weaker grade backgrounds may be considered if suitability for PhD education is documented. Good oral and written English skills are essential. Preferred qualifications include experience in scientific publishing, machine learning (especially distributed), coding and information theory, and communication networks/protocols. The position offers a gross salary of NOK 550,800 per annum, with a 2% statutory contribution to the State Pension Fund. The employment period is 3 years, and employees benefit from favorable terms as members of the Norwegian Public Service Pension Fund. Free Norwegian language training at a basic level (A2) is provided. NTNU offers a supportive and inclusive working environment, career guidance, and access to employee benefits. NTNU values diversity and aims to reflect the diversity of society in its workforce. The university encourages applications from candidates of all backgrounds, including those who have been out of work for a period of time. Measures are in place to promote equality and increase the proportion of women in scientific positions. To apply, submit your application and all required attachments electronically via Jobbnorge.no. Include transcripts and diplomas, CV, copy or draft of Master's thesis, documentation of completed Master's degree, motivation letter, publications, certificates, and contact information for three referees. Applications must be in Norwegian, a Scandinavian language, or English. Only applications received by the deadline will be considered. For questions about the position, contact Professor Kimmo Kansanen at [email protected] . The application deadline is 24th April 2026. The city of Trondheim offers a vibrant cultural scene, excellent welfare services, and opportunities for education, nature, and family life. NTNU’s Department of Electronic Systems is a leading academic environment in Norway, contributing expertise in areas such as nanoelectronics, phototonics, signal processing, radio technology, acoustics, satellite technology, and autonomous systems. Join NTNU and contribute to cutting-edge research in distributed machine learning and artificial intelligence.

just-published

Publisher
source

Kimmo Kansanen

University Name
.

Norwegian University of Science and Technology

PhD Candidate in Distributed Machine Learning

The Norwegian University of Science and Technology (NTNU) invites applications for a PhD Candidate in Distributed Machine Learning within the Department of Electronic Systems, located in Trondheim, Norway. NTNU is Norway’s leading technical-scientific university, with a strong focus on professional education and research excellence. The position is part of the SURE-AI national AI centre, a major initiative funded by the Research Council of Norway (2025-2030) to advance efficient, transparent, and safe artificial intelligence. SURE-AI brings together 19 Norwegian partners and researchers from 15 international institutions, fostering interdisciplinary collaboration and innovation in AI. The PhD project focuses on distributed machine learning, leveraging communication and distributed computing to utilize distributed datasets and computational resources. The research aims to address challenges such as network outages and computational bottlenecks, making distributed machine learning robust and scalable. The candidate will participate in SURE-AI project activities, contribute to academic publications and popular science dissemination, and engage with the signal processing group. International activities, including conferences and research stays, are encouraged. Applicants must hold a relevant Master’s degree (electronics, mathematics, data science, communication technology, or equivalent) corresponding to a five-year Norwegian course with 120 credits at the master’s level. Master students may apply if the degree is completed before 30.10.2026. A strong mathematical background, research-oriented master thesis, and an average grade of B or better (NTNU scale) are required. Admission to the Doctoral Programme in Electronics and Telecommunication is mandatory, and good oral and written English skills are essential. Preferred qualifications include experience in scientific publishing, machine learning (especially distributed), coding and information theory, and communication networks and protocols. The position offers a gross annual salary of NOK 550,800, with a 2% statutory contribution to the State Pension Fund, and membership in the Norwegian Public Service Pension Fund (SPK). Additional benefits include free basic Norwegian language training, career guidance, and a supportive, inclusive work environment. The employment period is three years, with the possibility of career promotion work. NTNU values diversity and aims to reflect the broader society in its workforce, promoting equality and inclusion. To apply, candidates must submit their application electronically via Jobbnorge.no, including transcripts and diplomas, CV, copy or draft of Master’s thesis, motivation letter, publications, certificates, and contact information for three referees. All documents must be in Norwegian, a Scandinavian language, or English. Applications are assessed only on information received by the deadline. For questions about the position, contact Prof. Kimmo Kansanen at [email protected]. The application deadline is 24 April 2026. Trondheim offers a vibrant cultural scene, excellent welfare services, and opportunities for education, nature, and family life. NTNU’s Department of Electronic Systems is a leader in fields such as nanoelectronics, phototonics, signal processing, radio technology, acoustics, satellite technology, and autonomous systems, contributing to national challenges in transport, energy, environment, and health.

just-published