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UiO/Anders Lien 1st August 2026 Languages English English English PhD Research Fellow-Continuous Experience Recognition for Distributed Co-creative Immersive Systems Apply for this job See
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Research Fellow-Continuous Experience Recognition for Distributed Co-creative Immersive Systems Apply for this job See advertisement About the position We invite applications for a PhD Research Fellow
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. Closing Date: 20 October 2026 The Role Applications are invited for a fully funded PhD position at Newcastle University as part of i3WaterS – Intelligent, Innovative and Integrative Water Systems, a
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Academic credentials: PhD in ecology, biology, statistics, computer science or engineering, or oceanography with a strong quantitative analysis background, particularly in species distribution modeling
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within the trenching team Contribute to site prioritisation, subsequent field planning, and broader project synthesis Job Requirements: PhD in geology, geoscience, Earth science, geotechnical engineering
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extending to 2100 and, where appropriate, 2300; develop and/or integrate hierarchical species distribution models and/or dynamic vegetation modelling approaches, using contemporary and historical biodiversity
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and the spatial distribution of potential reservoirs. This PostDoc position is part of the PEPR « sous-sol, bien commun » project IDYLLE (Impact of Lithosphere Dynamics and Basin Evolution
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 13 hours ago
research in distributed systems and software science. Our goal is to introduce greater autonomy into software systems' adaptation mechanisms, specifically to support the transition from adaptive to self
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, distributed control, multi-agent reinforcement learning, or mission planning. • Familiarity with real-time robotic systems and hardware-in-the-loop testing. • Experience managing
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distributed sensing technologies. The role will focus on distributed acoustic sensing on pre-existing telecom fiber networks, mobile sensing using vehicle fleets, multi-modal data fusion, and structural system