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Field
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looking for PhD Students in areas related to: Cybersecurity, Privacy and Cryptography Machine Learning and Data Science Efficient Algorithms and Foundations of Theoretical Computer Science Software
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reinforcement learning and evolutionary algorithms to balance emissions reduction, safety, commuter convenience, economic factors and policy evaluation to generate optimised sustainable mobility plans. Decision
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looking for PhD Students in areas related to: Cybersecurity, Privacy and Cryptography Machine Learning and Data Science Efficient Algorithms and Foundations of Theoretical Computer Science Software
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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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of the processing system online. Our approach will be to draw on a broad selection of tools including (deep) reinforcement learning, queuing networks, online algorithms and systems engineering. In addition, a large
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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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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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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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aims: Develop end-to-end protocols for screening selected foods and nutraceuticals. Create advanced strategies for data integration using tailored algorithms and machine learning approaches. Demonstrate
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theoretical research, algorithm design, and the development of software tools that demonstrate the applicability of the new methods. Research environment The positions are hosted by the Department