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aims to leverage quantum computing to address these challenges, focusing on developing novel quantum algorithms to enhance mRNA sequence design You will be co-supervised by leading experts in AI, data
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that may empower consumers to resist persuasion and reduce harmful consequences? Are you passionate about advertising, algorithms and social media? Then apply for this PhD project focused on demystifying
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advance scholarship on who is most often exposed to algorithmic persuasion, how different types of people cope and are affected, and how we can develop remedies to reduce negative consequences. By doing so
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efficiency. Your Job: Develop and apply meta-optimization that can automatically search for the best algorithm-hardware pair Tackle the challenge of computationally expensive meta-optimization procedures by
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Your Job: The conventional, manual co-design of algorithms and hardware is slow and inefficient. Our group develops methods and tools to automate the co-design process. The core of this project is
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to make viable trading decisions under high price volatility. This PhD position focuses on designing, developing, and evaluating self-learning energy trading algorithms that are able to cope with
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trading decisions under high price volatility. This PhD position focuses on designing, developing, and evaluating self-learning energy trading algorithms that are able to cope with these challenges. By
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-learning energy trading algorithms that are able to cope with these challenges. By leveraging real-time data, developed algorithms continuously adapt to market dynamics and respond to changing market signals
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you eager to make AI more sustainable? As a PhD Candidate, you will develop innovative methods for predicting and reducing the energy consumption of large-scale AI systems during their design phase
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demonstrated experimental realizations and proven theoretical advantages. The project may involve several aspects, including mathematical theory, algorithm development, error correction, adaptation of GBS-based