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UiO/Anders Lien 15th August 2026 Languages English English English PhD Research Fellow in computer science/AI for energy informatics Apply for this job See advertisement About the position We invite
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interactions. This involves (i) developing predictive machine learning models that forecast user actions and remote system responses across audio, video and haptic modalities, and (ii) jointly orchestrating
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page to watch video, or click here to open video) About the position The position is part of the research project “Prediction of genetic values and adaptive potential in the wild (GPWILD)” (https
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requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements: https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8 Grade requirements: The norm is as
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well as resource limitations. The core research objective of this PhD is to design and evaluate “latency hiding” methods for immersive networked interactions. This involves (i) developing predictive machine learning
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requirements, is provided below and in the links. Project descriptions Project 1: Predictive Bayesian inference and foundation models Employment: University of Oslo, Department of Mathematics PhD programme
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exemptions from the requirements: https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8 Grade requirements: The norm is as follows: The average grade point for courses included in
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, starting date, and project-specific qualification requirements, is provided below and in the links. Project descriptions Project 1: Predictive Bayesian inference and foundation models Employment: University
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predictive modeling and validation techniques. Research & Publication: Skilled at critically reviewing literature, designing rigorous studies, and producing publications for high-impact journals. Collaboration
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the Department of Geosciences. PHAB’s main goal, based on detailed studies of Earth and the solar system, is developing predictive models to identify habitable planets around other stars. Within three