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techniques and neural network techniques to adjust high-resolution X-ray spectra and infer physical properties of the emitting plasma. · Developing algorithms that optimise the adjustment of high-resolution X
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include the development and implementation of control algorithms on FPGA platforms, experimental testing using Hardware-in-the-Loop (HIL) setups, data analysis, and preparation of scientific publications
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Development, implementation and experimentation of distribution estimation algorithms in dynamic optimization problems. Where to apply E-mail lauragveiga@fi.upm.es Requirements Research FieldComputer science
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/Qualifications Experience in: - Development of artificial intelligent algorithms. - Explanaible artificial intelligence - LLM experience - Virtual intelligence entities using reinforced learning
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in medical image analysis. The ideal profile should demonstrate experience in developing deep learning algorithms applied to radiological imaging, particularly in breast and thoracic domains. Knowledge
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networks, deep learning or physiological signal analysis. - Minimum of 2 years of accredited professional or research experience in tasks directly related to: AI algorithm development, hardware/software
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Experience: In the development of medical devices in vision sciences. Implementation of psychophysical algorithms for vision. Design and analysis of clinical studies. Experience in functions similar to those
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The Brainlab – Cognitive Neuroscience Research Group (Universitat de Barcelona ) is seeking an outstanding candidate with strong motivation for the neuroscience of music and its impact on early development
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apply machine learning algorithms with special attention to digital footprint reduction and data privacy. Functions to be developed: Develop methodologies and experiments to measure and optimize
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estadísticos para su integración en plataformas de datos. --------------------------- Design and development of statistical data analysis algorithms for integration into data platforms. Where to apply E-mail