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, electrical & electronic engineering, or equivalent. Background knowledge in signal representation/processing, visual data compression, and data-driven and machine learning/analysis. Prior research experience
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the High Performance Computing and Data Center, to be completed on campus by August 2026. This position collaborates with others in the growing machine learning and exoplanet subgroups within the Physics and
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Supervised Machine Learning and Reinforcement Learning. The objective is to significantly enhance battery performance and longevity. While conventional methods rely on either physics-based models or high-level
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spatial transcriptomics and imaging genomics projects, integrating bulk and single-cell RNA-seq datasets, and applying advanced statistical and machine-learning methods (AI/ML) to extract novel biological
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. The role will focus on developing machine learning and mathematical optimization solutions for electric vehicle fleet charging optimization under different constraints. Key Responsibilities: Formulate
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spatial transcriptomics and imaging genomics projects, integrating bulk and single-cell RNA-seq datasets, and applying advanced statistical and machine-learning methods (AI/ML) to extract novel biological
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/2025 Role Description An exciting opportunity for an established researcher or a recently completed PhD researcher with experience in malacology, epidemiology, data mapping and/or schistosomiasis
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challenges from low carbon shipping and sustainable fuels to solar power technologies and advanced brain models. Learn more at https://mecheng.ucl.ac.uk . Within this dynamic environment, the Moazen Lab is
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material design process. Some potential key research objectives: AI Model Development: Create machine learning models to predict FGM properties based on compositional gradients and processing conditions
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bone marrow transplantation. We are looking for a highly motivated candidate with a PhD degree interested in using microbiological methods with the aim of developing novel strategies to improve bone