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the results of which would be used to enrich the available experimental data in order to develop a Design for Manufacture and Performance concept based on machine learning algorithms where the required
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argon. The analysis of the ProtoDUNE data will help to validate calibration techniques and particle identification algorithms. The candidate should have a good knowledge of particle physics and experience
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osteoporosis, osteoarthritis and bone metastases. In particular, you will join other six researchers (postdocs, PhD students and technicians) to work on the Virtual Mouse to Human Twins for Osteoporosis (VMHTsOP
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Deadline: 31 October 2025 Details This project aims to develop new algorithms for reinforcement learning from human feedback, to effectively solve complex reinforcement learning tasks without a predefined
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electromagnetic design. We will explore advanced topologies for mmwave metasurfaces, design novel reconfiguration mechanisms, and develop intelligent algorithms to optimize scattering characteristics in real-time
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processing, data analysis, data-driven modelling, optimisation and computation algorithms, machine learning models and neural network structures, as well as strong skills and experiences in computational
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presentation of own research data. Provide support to lab PI and postdocs engaged on the project Take responsibility for the day-to-day experiments, including windowing/staging of chick embryos, in vivo
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seminars, including presentation of own research data. Provide support to lab PI and postdocs engaged on the project Take responsibility for the day-to-day experiments, including windowing/staging of chick
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on specific use cases, including multi-modality perception systems, to enable testing and validation of robotic manipulation strategies. Implement intelligent algorithms for the robotic execution
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Nonlinear Distributed Control