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Field
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research subject for this position is development of distributed processing strategies and algorithms for Large Intelligent Surfaces, including both joint baseband processing and synchronization across
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and automated sensors to genetic techniques and classical field-based inventories. This PhD project focuses on how biodiversity in forests can be measured, monitored, and analysed. The position is
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. The following education, experience and expertise are required: solid knowledge in machine learning, optimization, or algorithm development programming experience, preferably in Python In addition, the following
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position within a Research Infrastructure? No Offer Description Project description Third-cycle subject: Computer Science We are looking for two highly motivated individuals to pursue a Ph.D. in algorithms
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for geometry assurance – integrating live sensor geometric sensor data with simulation for real-time control and adaptive assembly. This builds on existing work within the group on digital twins for geometry
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sensor geometric sensor data with simulation for real-time control and adaptive assembly. This builds on existing work within the group on digital twins for geometry assurance. AI for automatic tolerance
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, and providers of enabling technology, e.g. sensors and AI for data capture and analysis, respectively. Who we are looking for The following requirements are mandatory: To qualify as a doctoral student
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the world, ii) developing AI+Physics end-to-end reconstruction algorithms that will enable a new regime of spatiotemporal hierarchical characterization. The project is mainly computational with
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Do you want to contribute to groundbreaking research in the development of a theoretical framework and numerical algorithms for evolving stochastic manifolds? This is an exciting opportunity for a
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and significant piece of information to the right point of computation (or actuation) at the correct moment in time. To address this challenge, you will focus on developing theoretical and algorithmic