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Description Implement and validate machine learning models and statistical algorithms for data imputation, anomaly detection and uncertainty management in geospatial environments. Collaborate in the preparation
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research grant Refª BI|2025/802 Project ATE – Refª C644914747-0000023 funded by Recovery and Resilience Plan (RRP) https://recuperarportugal.gov.pt/ and Next Generation EU European Funds Application
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formula is true or false (EXPTIME vs NP). Can we develop and implement efficient algorithms for this problem? This problem has been attacked using multiple different methods for the past 40 years, without
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frameworks such as COLMAP and Open3D; Ability to develop algorithms for object detection and tracking, 3D reconstruction, and SLAM. Advanced Control and Intelligent RoboticsSolid knowledge of classical and
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to facilitate perceptual learning of different stimulation patterns; and (iii) the development of advanced AI algorithms capable of converting camera input into real-time electrical stimulation parameters. In
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algorithmic innovation and robot deployment, leading experimental design, system integration, and evaluation on real robotic platforms. The Embodied AI and Robotics Lab (AIR) develops intelligent robotic
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, diverse and UK-wide research programme in probabilistic AI, developing the next generation of mathematically principled, scalable and uncertainty-aware AI algorithms. This will be achieved by bringing
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participants of the Netherlands Twin Register, integrating genetic and psychological data where relevant. Beyond algorithm development, you will also address methodological challenges such as data quality, bias
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programme Reference Number AE2025-0503 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0503
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Leverhulme Centre for Algorithmic Life Fellows - Assistant Professor (Research) G7 - G8 ( Job Number: 25001667) Department of Geography Grade 7/8: - Grade 7: £38,784 to £46,049, Grade 8: £47,398