427 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" "Univ" scholarships in United Kingdom
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-making autonomy and human-machine teaming. The use of logic and data to make decisions, solve problems, and learn. Moving from rule-based systems to agents with strategic flexibility. The range and
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(Master / PhD / Postdoc). Our expertise lies in quantum foundations, quantum information theory and quantum technologies. For additional information, please visit: https://dakic.univie.ac.at/ . Your future
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: https://events.teams.microsoft.com/event/376b2195-d8da-47c0-86e2-b18813ec19e3@4a5378f9-29f4-4d3e-be89-669d03ada9d8 . Number Of Awards 1 Start Date 1st October 2026 Award Duration 3.5 years Application
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framework integrating physics-informed machine learning, scenario generation, and human-in-the-loop preference-based reinforcement learning to prioritise climate-robust and equity-aligned interventions
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with NEOM, one of the world’s largest ecological restoration programmes, the project will develop machine-learning approaches to analyse satellite observations of vegetation change and evaluate large
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programming (e.g., Python/C++), machine learning frameworks, or robotics software environments such as ROS. You are motivated to work in a multi-disciplinary research environment combining engineering, AI, and
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training programme at the start of the PhD to develop skills in areas such as programming, data analysis, machine learning and signal processing. This will provide the technical foundation required to work
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expertise in programming (C++, Python), computer architectures and Deep Learning (PyTorch, TensorFlow). Exceptional international candidates may be eligible for a fee waiver (read the following section
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network integration for emerging low-energy opto-electronic AI systems and beyond. The challenge: Machine learning and neural networks are super-charging the complexity of problems that computer algorithms
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language processing, statistical machine learning and causal inference. The scholarship will fund course fees up to the value of home fees*, a tax-free stipend of no less than £20,780 per annum), plus additional