31 data-"https:"-"https:"-"https:"-"https:"-"https:"-"embl" Postdoctoral positions in Saudi Arabia
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Exploitation Group at KAUST. The focus of the position will be on the development of new methods integrating a variety of data types (remote sensing, geology, geophysics, geochemistry) for geological
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Rohrbach and T Tuytelaars Code: https://github.com/rahafaljundi/MAS-Memory-Aware-Synapses Theme C Vision&Language learning (selected papers): VisualGPT: Data-efficient Image Captioning by Balancing Visual
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, Data Science and/or Nutritional epidemiology to join an interdisciplinary project aiming to understand how the nutrient contributions of aquatic foods vary across space and time—globally and with a
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learning using 3D data. More information about the research group and KAUST can be found under the following links: http://peterwonka.net/ https://cemse.kaust.edu.sa/vcc https://www.kaust.edu.sa/en If you
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King Abdullah University of Science and Technology (KAUST | Saudi Arabia, | Saudi Arabia | about 2 months ago
well as to allow video information to be shared for both marketing, analytics and editorial purposes. By accepting optional cookies, you consent to the processing of your personal data - including
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reef fisheries. In doing so, we will also establish a long-term, market-based monitoring program, generating real-world data to inform smarter, fairer, and more sustainable management of reef fisheries
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postdoctoral scholars. Successful candidates will conduct research on the synthesis of nanomaterials for applications in energy and the environment. Submit your CV at https://kaustforms.formstack.com/forms
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safety, documentation, data management, and timely reporting. Publish high-impact papers, present at conferences, contribute to proposals where appropriate, and mentor students. Compensation Package
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protocols for cell fabrication (especially pouch where applicable), quality control, and data management. Prepare technical reports, manuscripts, and conference presentations; contribute to proposal
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usually attributed to the limitations in our measurements and in the underlying physical models. Machine learning (ML) techniques can be exploited to identify common patterns in the data and augment the