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We are seeking a Postdoctoral Researcher in Human-AI interaction to join a research group focused on studying learning and decision-making in humans and machine learning systems led by Prof Chris
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, molecular diagnostics and novel treatments of lung diseases. The Centre offers a vibrant, inclusive, collaborative, and interactive environment. The postholder will interact with clinicians based at the Royal
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, molecular diagnostics and novel treatments of lung diseases. The Centre offers a vibrant, inclusive, collaborative, and interactive environment. The postholder will interact with clinicians based at the Royal
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machine learning, computer vision, human-computer interaction, or similar relevant areas. Experience in research or development on bias, interpretability, and/or privacy in machine learning/AI is necessary
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for energy efficient hardware such as RISC-V The opportunity to interact with high performance computing companies like NVIDIA, XILINK (AMD) and HPE The opportunity to contribute to Xcompact3d, an open source
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to interact with high performance computing companies like NVIDIA, XILINK (AMD) and HPE. The opportunity to contribute to Xcompact3d, an open source framework of flow solvers dedicated to the study of turbulent
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Institute for Molecular and Computational Medicine (IMCM). You will test GSK assets and targets in established models of podocyte and mesangial cell pathology relevant to glomerular diseases. You will
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connectome, with a focus on the chemosensory circuits involved in human host-seeking. The principal focus will be on the high level proofreading, annotation and analysis of connectomics data. This will include
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Mathematics), the post holder will interact with researchers in statistics and machine learning at Royal Holloway, the Biophotonics Group at the University of Nottingham, clinicians at the Nottingham Breast
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-quality robotics research in the areas of robot grasping and manipulation, kinematics and mechanisms, sensing, and human-robot interaction. Within CORE, SAIR focuses on multimodal machine learning for human