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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
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Approximation. Parameterized Complexity is a vastly growing area within theoretical computer science that allows for the development of exact and approximation algorithms for computationally hard problems by
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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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integrates machine learning and statistics to improve the efficiency and scalability of statistical algorithms. The project will develop innovative techniques to accelerate computational methods in uncertainty
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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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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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Join us for this exciting self-funded PhD studentship on " Development of Sustainable and Cost-Effective Coatings to Mitigate Battery Thermal Runaway Propagation" in collaboration with
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and one Postdoctoral position in the field of robot motion and control algorithms for soft material handling, starting September 2025. We are seeking highly qualified and motivated individuals with a
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(Artificial Intelligence and Epidemic Modeling to Prepare Hospitals for the Next Respiratory Pathogen with Pandemic Potential). Project Overview The COVID-19 pandemic exposed critical gaps in our ability