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is to develop machine-learning-based algorithms for transmitter pre-distortion and receiver post-distortion architectures that enable distortion-free quantum communication systems. A key focus will be
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approaches, such as topology optimization, with gradient-free methods, such as genetic algorithm, in order to exploit the specific strengths of the two classes of algorithms, and through this reach an ideal
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communication infrastructure design and evaluation, reliable communication technologies, protocols and algorithms, internet of things and wired/wireless communication at all network layers. The candidate should
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simulation tasks. A key objective will be the development and testing of algorithms for gas hydrate phase equilibrium calculations. CapSim seeks to advance CO₂ capture simulation technology by enhancing
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motivated to move the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our team, you get the opportunity to use the latest algorithms in machine learning
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Job Description Are you interested in quantum computing? Do you have a keen interest in developing your skills in developing algorithms and software and build the quantum computing infrastructure in
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development, and computational algorithms A solid understanding of theoretical chemistry and solvation models such as COSMO The ability to work independently as well as collaboratively within a
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will be an asset. The PhD will be supervised by Professor Helene Friis Ratner and conducted as part of the Algorithms, Data and Democracy project, founded by the VELUX Foundations. For more information
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-disciplinary involving algorithmics, stochastic optimization, multi-criteria decision making, and data science. As part of the project, you will implement and test algorithms and further develop your skills in
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. You will support field behavioral experiments to test designs of tradable credits schemes in specific urban contexts. You will explore and implement machine-learning algorithms and classical dynamic