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Start Date: October 2026 Application deadline: 30th April 2026 Introduction: Warm cumulus clouds have been observed to yield precipitation as soon as 30 minutes after their formation. Formation
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. "Studying the origin of the new discovered class of weak CN stars in the Magellanic Clouds using stellar variability" "How do stars merge? Studying the merger between low and intermediate-mass main-sequence
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Intelligence (AI) and Machine Learning (ML) capabilities into distributed cloud-edge infrastructures to enable autonomous and efficient network/service management. The PhD candidate will investigate innovative
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assessments: both predictions and reference data change over time, requiring methods that account for temporal misalignment. Variable observation density: seasonal cloud cover, satellite revisit times, and
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for next-generation (6G) communication systems. The project focuses on integrating Artificial Intelligence (AI) and Machine Learning (ML) capabilities into distributed cloud-edge infrastructures to enable
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where networks reason, negotiate, and self-manage across edge-cloud environments. What you will do (Responsibilities) As part of the Software Networks group and a network of 15 international researchers
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that enable networks to autonomously mitigate failures and to dynamically adapt to changing conditions, while ensuring reliable service delivery across cloud/edge/terrestrial/non-terrestrial infrastructures
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service delivery across heterogeneous infrastructures, including terrestrial and non-terrestrial networks, cloud-edge environments, and vertical industry domains. The PhD candidate will investigate
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will be supervised by Assoc. Prof. Larissa Beumer (UNIS, main supervisor) and Prof. Leif Egil Loe (NMBU, co-supervisor). Assoc. Prof. Eero Rinne (UNIS, Geophysics Department), Prof. Tobias Ullmann
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ensuring reliable service delivery across cloud/edge/terrestrial/non-terrestrial infrastructures. You will publish scientific articles related to the research project. You will carry out a limited number of