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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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THR demand in younger patients expected to increase fivefold by 2030, revision surgeries will also rise. To improve implant positioning, image-guided navigation is increasingly used in complex THR
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the scalability and robustness of AI in complex environments which is a major step towards the digital transformation of the manufacturing industry. Motivation Automation is key to meeting the growing demand
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semiconductor devices, large antenna arrays for satellite communication, and advanced electromagnetic surfaces with unconventional material properties. As these devices continue to become more complex and operate
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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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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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collaborators that: Negotiate more effectively by anticipating the downstream effects of each statement. Support complex decision-making in domains where success depends on multi-step strategy. Learn to adapt
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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