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Spaces Sciences at the University of Washington seeks a Postdoctoral Scholar to work on numerical simulations and data analysis to inform the search for life on exoplanets. The position will be supervised
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, neuroscience and personalised medicine. The Department of Biomedicine provides research-based teaching of the highest quality and is responsible for a large part of the medical degree programme. Academic staff
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and archival data, as well as working towards future observing proposals and strategies. Within this framework, the successful candidate will have flexibility and freedom to tailor the project
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training algorithms and AI architecture. Image reconstruction, segmentation, and classification. High performance computing for spatiotemporal data. Major Duties/Responsibilities: Develop foundation AI
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term role to support a large project looking at developing outdoor thermal comfort models for children? If so, we would welcome your application to this full-time, fixed term role. As a Post-doc Research
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) information-theoretic active learning, and c) capturing uncertainty in deep learning models (including large language models). The successful postholder will hold or be close to the completion of a PhD/DPhil in
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on X-ray scattering data (e.g. powder diffraction, pair distribution function (PDF), single-crystal), preferably with experience in situ/operando characterization and large user facilities such as
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large multi-dimensional datasets using statistical tools such as positive matrix factorization (PMF) and cluster analysis Investigate the influence of different urban emission sectors on atmospheric
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using experimental data from laboratory setups Validate models through targeted measurements and structured testing procedures Analyse loss mechanisms and system efficiencies under various operating
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with the possibility of renewal. This project addresses the high computational and energy costs of Large Language Models (LLMs) by developing more efficient training and inference methods, particularly