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. Research Environment The project is in collaboration with two partners: (i) IDCOM at the University of Edinburgh, which develops theory, algorithms and hardware for the next generation of signal processing
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aims to optimize the operations (serving) of AI by developing algorithms that manage compute, network, and storage resources in a carbon-efficient way while supporting long-term benefits
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for Artificial Intelligence (FCAI), ELLIS Institute Finland, and Aalto University House of AI, invites applications for multiple postdoctoral positions. Our team works actively to develop intelligent robotic
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algorithms. The research focuses on wind energy applications, creating a compelling sustainability narrative: developing more efficient computational methods to optimize wind farm performance, which in turn
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aims to develop formal frameworks and algorithms for eliciting, aggregating, and analysing stakeholder preferences over risk and safety in AI systems. The Research Assistant will support the development
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fundamentally more energy-efficient Computational Fluid Dynamics algorithms. The research focuses on wind energy applications, creating a compelling sustainability narrative: developing more efficient
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and evaluation. The post holder will take a leading role in advancing theoretical and algorithmic research in the domain of probabilistic preference aggregation, contribute to the design and analysis
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Experience in devising and developing novel machine learning algorithms Hands on experience with ROS and physical robots Excellent mathematics skills, particularly in areas relevant to robotics and AI
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-disciplinary research environment Desirable criteria 1. Experience in devising and developing novel machine learning algorithms 2. Hands on experience with ROS and physical robots 3. Excellent
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dynamics, solid mechanics, soft matter or active matter. • To become familiar with simulation algorithms as needed, assist in the development of new ones, test and document any newly developed