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INESC TEC is accepting applications to award 4 Scientific Research Grant - NEXUS - CTM (AE2025-0564)
; - Collaborate in the writing of technical reports regarding the protocols, mechanisms, and algorithms developed; - Co-author scientific publications based on the work developed; - Prepare the research grant
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Liu at UA Department of Geography and the Environment. The postdoctoral scholar will lead sediment remote sensing algorithm and foundation model development and implementation, remote sensing and field
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. Its role is pivotal in the overall performance and safety of the vehicle, underscoring the importance of our work in this field. Various algorithms, models, and signals control different components
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the preparation of technical reports on the algorithms, mechanisms, models, or protocols developed; - collaborate in the development of new communications solutions for extreme environments; - contribute to co
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algorithms. The aim is to develop a high-performance intelligent motor control system that enables greater sustainability, safety and efficiency of the e-bike's energy system, in order to meet the requirements
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environmental sensing. The incumbent will contribute to the development and deployment of real-time correction algorithms and hardware systems, leveraging GLAO technologies in collaboration with ULTIMATE-Subaru
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models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees. Research areas include Representation Learning, Machine learning and Optimization
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between historical methods underpinning modern data science, which were developed for significantly different contexts and applications than current AI-driven business use cases. Postdoctoral Fellows at D^3
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approached by tools in both computational chemistry and applied mathematics. Specifically, the project involves the development of mathematical modeling strategies at both numerical and analytical level to
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of information in their daily lives - from local news to institutional messaging and algorithmically curated feeds. We are investigating how trust forms, erodes, and gets repaired, and how technologies