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researcher with expertise in communication, project management, and leadership. You will build a robust national and international network and acquire advanced knowledge essential for implementing critical
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supporting the Net Zero 2050 target. This PhD project will develop an AI-enabled framework that optimizes wind turbine control and predictive maintenance. Using Deep Reinforcement Learning (DRL), the system
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The Intelli-Ingest Doctoral Network is an EU-funded Marie Skłodowska-Curie Action (MSCA) initiative is a network bringing together leading academic, clinical, and industrial partners to train a new
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Human-AI interaction. Your network and team The Aalto Engineering Psychology Group concentrates on research in human-AI interaction . Currently, research activities focus on applying research methods from
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neuroscience and data analysis Proficiency in programming (e.g., Python, MATLAB, and similar languages) Experience with large-scale neural network simulations Experience with analysing large-scale neural
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models considering networks of patches and their species and interactions composition to predict spatial and temporal community structure across restoration gradients, aimed at developing a predictive
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to improve structural durability, reduce material consumption, and support the UK’s net-zero goals. Funding notes: The position includes a full scholarship for UK-based PhD candidates and a half-scholarship
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including machine learning. This research will support the path to net zero flights and there will be opportunities to become involved in practical aspects of fuel system design and testing during their PhD
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, potentially including machine learning. This research will support the path to net zero flights and there will be opportunities to become involved in practical aspects of fuel system design and testing during
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labs framework. This studentship will include cohort-based training and activities, enabling students to gain wider skills and develop valuable personal and professional networks. Project Description