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programme Wireless Communications; as per January 1, 2027, or as soon as possible thereafter. In electronic engineering, Aalborg University is known worldwide for its high academic quality and societal impact
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plant phenotyping, microbiome profiling, predictive modelling and targeted experimental validation to identify the microbial factors that make plants more resilient to disease. Your job You will join the
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, can be transferred to work directly on experimental measurements. In this PhD, you will develop AI-driven ultrasonic methods for quantitative materials evaluation, focusing on inverse models
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are optimized based on plant performance and energy price fluctuations. The learned models and resulting data-driven control approaches will be designed to be more easily transferable between different
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
knowledge of AI-enhanced planning in shipbuilding supply chains. Apply quantitative methodologies, such as simulation, analytical modelling, and AI‑driven techniques, to develop decision support for efficient
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– Atmosphere” (TOSCA) domain of the CNES. Since 2011, the GET has also been an affiliated unit and a component of the Carnot Institute ISIFoR (Sustainable Engineering of Georesources). This project aims
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AITHYRA GmbH - Research Institute for Biomedical Artificial Intelligence of the Austrian Academy of Sciences | Vienna, Virginia | United States | about 15 hours ago
Intelligence and the Life Sciences. We are building an AI-native, closed-loop research engine where automation, computation, and intelligent agents work together to decode, model, and rewrite biological circuits
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6 Sep 2026 Job Information Organisation/Company NTNU Norwegian University of Science and Technology Department Department of Ocean Operations and Civil Engineering Research Field Engineering
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image data. The research explores how AI-driven analysis can move beyond manual reverse-engineering workflows by automating feature extraction and structural interpretation while remaining robust to noise
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. Faculty Mechanical Engineering From chip to ship. From machine to human being. From idea to solution. Driven by a deep-rooted desire to understand our environment and discover its underlying mechanisms