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no later than October 1, 2026. No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo. The position is placed in the Digital Signal Processing and Image Analysis
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. This mutation abolishes opioid receptor signaling and offers unprecedented insights into how μ-opioid signaling shapes addiction risk. This PhD project (Work Package 4) aims to use advanced computational methods
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Technology, Sound Engineering, Audio and Signal Processing, Psychology, or other fields relevant for the position, before the date of employment. Candidates that are close to completion may also be evaluated
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UiO/Anders Lien 1st March 2026 Languages English English English PhD Research Fellow in Natural Language Processing Apply for this job See advertisement About the position Position as PhD Research
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ARRAKIHS satellite mission with the main goal of understanding the impact of dark matter models and baryonic processes in faint substructures (e.g., dwarf satellites and stellar tidal streams) around disk
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partitioning for parallel/distributed AI/ML Optimization of process-to-process communication in parallel/distributed AI/ML Enhancement of AI/ML with in-network computing & processing Adaptation & optimization
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planetary systems Stellar physics and/or geophysics with a strong background in computational methods and signal processing. 5. Project: Revisiting the young faint Sun problem Space physics, climate
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to the project using semiconductor processing and quantum technology. The PhD Research Fellow will be affiliated with the Solid State Physics and Quantum Technology group with around 60 highly dedicated professors
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warming Arctic, processes such as permafrost thaw, changing landscape morphology, altered infiltration patterns, are reshaping groundwater systems. These physical changes in turn drive chemical responses
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understanding of how acoustic waves are generated and transmitted in wells. The LeDAS project aims to overcome these challenges by combining physical modelling, advanced signal processing, and machine learning in