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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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focus will be on developing compact, efficient, and real-time LLM algorithms/hardware on the edge and developing demos for specific applications such as speech disorder therapy. Your responsibilities will
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of computer science; You’re enthusiastic about (and ideally experienced in): inference algorithm development and evaluation for statistical computing and machine learning; applications of statistical computing and
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is to increase donor organ utilization through merging cell therapy techniques with state-of-the-art organ perfusion strategies. PhD project The aim of the PhD project is to develop and implement a
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Applications are invited for a fully-funded four-year PhD position that will explore how rural youth (ages 18–30) use both online and offline methods to make sense of sustainable development and the
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PhD position on decadal coastal dune development Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 36 to 40 Application deadline: 8 September 2025
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temporarily, as needed, when needed. The goal of this project is to advance the understanding of how working memory is implemented in the human brain. To this end, the main objective is to develop a neural