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Field
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at NSLS-II seeks a postdoctoral researcher with a strong background in computational imaging, data science, or scientific computing. This position will focus on developing advanced image reconstruction
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Barcelona is seeking a highly motivated Computer Engineer to join our team and contribute to the development of a cutting-edge federated analysis infrastructure for the European repository of cancer imaging
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historical data. You will evaluate the performance of these models on real industrial cases in order to propose a demonstrator or prototype that can be used in production. Where to apply Website https
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, embedded controllers, and closed-loop control routines on prototype hardware; preparing technical reports, delivering presentations to stakeholders, and contributing to journal and conference publications
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(e.g., PyTorch, TensorFlow, JAX), and scientific libraries (e.g., NumPy, SciPy, scikit-learn) Familiarity with medical images such as x-ray, CT, or fluoroscopy. Proficiency in Python coding language and
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, laser-induced pattern formation or self-organisation, pump-probe or ultrafast imaging techniques, plasma diagnostics, hands-on work with ultrafast laser systems. Strong scientific communication skills in
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period of 12 months in the first instance, with potential to extend. The project involves advanced theory for new ultrafast imaging experiments and is funded by Engineering and Physical Sciences Research
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experience in the document image analysis field. The applicants are expected to be fluent in both oral and written communication in English. They should work well in a team while demonstrating initiative and
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implement cutting-edge AI solutions for real-time, image-guided medical applications, with a focus on advanced robotics. You will work directly with clinical data to design robust, efficient deep learning
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objective of this project is to compare the modern philosophy of Bildung and the contemporary paradigm of the Learning Society (LS) by systematically analyzing their homological structures. Through