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learning algorithms on graphs to model, characterize, predict, and design the thermal and physical behaviors of diverse material systems. Responsibilities also include the development of software codes
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beginning May 2025 to conduct research under the supervision of Prof. Nick Laneman and collaborating with other leading faculty in the ND Wireless Institute and SpectrumX, the NSF Spectrum Innovation Center
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design, development, and validation of material, control systems, and algorithms for next-generation soft haptic actuators and experiences. Note that the research involves significant interactions with
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with data science, and data management (including IoT, Edge, and HPC). This is a fully funded position for 12 months within the HEXAPIC project, conducted in collaboration with Prof. Leon Kos' team
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collaboration with Prof. Giovanna Tinetti and her team and collaborators at KCL. The main purpose of this role is to develop new and/or to use existing models to simulate the atmospheres of exoplanets and use
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classification for hyperspectral and fluorescence lifetime datasets. Optimize algorithms for batch processing and scalability, enabling high-throughput, automated analysis of large image datasets from fluorescence
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algorithms for the scanner using machine learning and deep learning. Qualifications: The position requires some background in machine learning, optimization, and deep learning. Some familiarity with MR physics
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About the role We have an exciting opportunity to join the Rare Genetic Disorders Research Group led by Prof. Stephan Sanders in the Department of Paediatrics at the University of Oxford as a Full
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multi-agent autonomous systems and related technologies. This will include development of distributed monitoring algorithms enabling agents in a multi-agent swarm to autonomously locate other agents in
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Alexandria, Virginia. The focus of these positions will be on quantum computing, quantum algorithms, quantum learning, quantum error correction, and quantum fault-tolerance. The successful candidate will join