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methods to improve the deployment, adaptation capabilities and safety of robots and critical infrastructures. The developed algorithms will be evaluated on legged robots, wheel-based robots and under
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About Us We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with
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deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with experience in: Deep learning Medical imaging computing
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EPSRC-funded project, MAPFSI that will be focused on developing experimentally-validated computational algorithms for fluid-structure interaction problems including multiphysics effect of electromagnetism
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of the fingers, and the positions of tactile sensors), and the control policy for that hand, when given a particular task or set of tasks. Through this, we aim to develop a framework that can automatically
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Engineering or a related field. In this role, the selected candidate will be responsible for designing, developing, and optimising algorithms for processing and analysing signals in real-time applications
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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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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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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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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