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of fully autonomous navigation systems. Main responsibilities Develop and optimize autonomous navigation algorithms for outdoor mobile robots. Integrate and fuse data from perceptual sensors (LiDAR, RGB
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FOR DRAWING UP OF PREDOCTORAL CONTRACTS FOR THE TRAINING OF DOCTORAL STUDENTS FUNDED BY THE UPV'S RESEARCH STRUCTURES – SUBPROGRAMME 2 (PAID-01-22) 119865 Development of machine-learning and graph-based models
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STUDENTS FUNDED BY THE UPV'S RESEARCH STRUCTURES – SUBPROGRAMME 2 (PAID-01-22) 119977 Development of mathematical and machine-learning algorithms to support an intelligent, integrated system for biosafety
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group is searching for a Research scientist position focused on iterative phase reconstruction algorithms and analysis of time-resolved coherent diffractive imaging datasets. Job description We
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for three consecutive periods (2014-2018 and 2018-2022 and 2023-2026). ICN2 comprises 20 Research Groups, 7 Technical Development and Support Units and Facilities, and 2 Research Platforms, covering different
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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