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. The researcher is expected to have (i) strong machine learning skills to improve model performance and robustness, and (ii) exemplary passion and motivation to pursue multidisciplinary research at the intersection
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degree in computer science (or a related field) Rich experience in devising machine learning models, methods, and algorithms for computer vision and image processing. Scientific track record with
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samples. The candidate will have the opportunity to work directly with experimentalists to validate predictions made by their machine-learning models, and to develop user-friendly tools that will be used by
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. Stefanos Zafeiriou can be found at https://wp.doc.ic.ac.uk/szafeiri/ . Research Associate: A PhD (or be close to completion) in an area pertinent to the subject area, i.e. computer vision, machine learning
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University More Jobs from This Employer https://main.hercjobs.org/jobs/21931781/temporary-online-course-developer-rhin-xxx-clinical-data-science-and-machine-learning Return to Search Results
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this limitation in the use of satellite observations by make a direct use of radiance observations retrieved by satellites using machine learning without the need of radiative transfer calculations. The new model
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engineeringEducation LevelPhD or equivalent Skills/Qualifications We are seeking a scientist with: Expertise in image-based biological tissue modeling and simulation Good command of deep learning Expertise in coding and
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climate will warm and recover in a net-zero future. As part of this project, you will apply machine learning (ML) methods to discover reduced-order models from data and develop GenAI-based techniques
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. Integrate physical laws, experimental data, and simulation results into unified machine learning frameworks to improve model robustness and generalizability. Conduct data preprocessing, model training, and
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large-sample hydrology (LSH) datasets, deep learning rainfall-runoff models, and hydrological alteration analyses, with the ultimate goal of improving the identification and management of ecological flows