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Field
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for greater precision. Machine learning (ML) algorithms will analyse these datasets to deliver a scalable, cost-effective system, validated through field trials and enhanced by contributions from four
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we
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analytics, anomaly detection, and embedded redundancy to enhance system resilience. Students will focus on creating adaptive algorithms and hardware implementations that enable real-time diagnostics and
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CST Microwave Studio, HFSS or EM Pro for antenna modeling and design is required, as is experience with programming languages like MATLAB, Python, or similar for antenna array analysis and algorithm
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of software interfaces and data models Selection and configuration of algorithms for annotating and organizing research data and software using state-of-the-art AI technologies Ensuring the sustainability and
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achieve automated data driven optimization (in terms of time and quality) of polishing process parameters by application of machine learning algorithms, leading to a robust, repeatable and fast polishing
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PhD Stipends within Distributed, Embedded and Intelligent Systems (DEIS) At the Technical Faculty of IT and Design, Department of Computer Science, one PhD stipend is available within
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of superconducting qubits to quantify performance and identify limiting physical mechanisms Perform quantum device calibrations, benchmarking, and run quantum algorithms Presenting and publishing the research
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Karolinska Institute. About us The Department of Computer Science and Engineering (CSE) is a joint department between Chalmers and the University of Gothenburg and is internationally recognized for its
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slicing. - Develop advanced AI/ML algorithms and data analytics techniques to automate and optimise exposure requests, adapted to available resources and real-time demand. - Propose and