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Field
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relevant environments. What we are looking for: PhD (or near completion) in Robotics, Artificial Intelligence, Computer Science, Control Engineering, or a related discipline; candidates without a PhD will be
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PhD position in Adaptive Protocols for Decentralized Wireless Networks - Secure Mobile Systems Group
. Römer. Leveraging Cross-Technology Broadcast Communication to build Gateway-Free Smart Homes, 17th International Conference on Distributed Computing in Sensor Systems (IEEE DCOSS). 9 pages. 2021. https
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economy-wide modelling. Assess the distributional impacts of network investment using macroeconomic models such as Input Output and Computable General Equilibrium. There is a unique the opportunity to gain
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through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The Universidad de Las Palmas de Gran
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Infrastructures Didactics of Informatics Digital Humanities Distributed Systems High-Performance Storage Machine Learning Medical Informatics Neural Data Science Practical Informatics Scientific Information
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, amongst other applications. However, application specific operational drawbacks can have detrimental impacts on conversion, selectivity and uniformity of product distribution, such as in solid precipitates
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One of the essential networks for society is water distribution networks. The delivery of water to customers is affected through different threats to the system. These include failure of components
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20 Feb 2026 Job Information Organisation/Company NOVA.id.FCT- Associação para a Inovação de Desenvolvimento da FCT Department Nova-Lincs Research Field Computer science » Informatics Researcher
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We are seeking a highly motivated candidate to undertake a PhD program titled "3D Temperature Field Reconstruction from Local Temperature Monitoring in Directed Energy Deposition." This exciting
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research program that brings together physics, chemistry, and machine learning. Your research tasks will include: Uncertainty Estimation in Deep Neural Networks for MLFFs Implement and test uncertainty-aware