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We are seeking a full-time Postdoctoral Research Assistant in Computer Vision to join the Visual Geometry Group (Central Oxford). The post is funded by ERC and is fixed-term for 1.5 years with a
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sustainable alternative to conventional rubbers, thanks to their re-processability, recyclability, and design flexibility. A micromechanical approach will be adopted to link key microstructure parameters (hard
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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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and leading a programme of numerical simulations relating to all aspects of our research on P-MoPAs; using particle-in-cell computer codes hosted on local and national high-performance computing
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The post holder will develop computational models of learning processes in cortical networks. The research will employ mathematical modelling and computer simulation to identify synaptic plasticity
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With the human population estimated to reach 9.8 billion people by 2050, the looming nitrogen (N) crisis, stemming from the intensive use of fertilisers in agriculture, requires urgent global action
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experts to acquire bespoke training and testing data; develop prototype solutions informed by the latest ideas in medical imaging AI, computer vision and robotic guidance; and evaluate models in simulated
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learning, at the intersection of reinforcement learning, deep learning and computer vision, in order to train effective robotic agents in simulation. You should hold a relevant PhD/DPhil (or near completion
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computer programs to design experimental paradigms, analyse data and conduct advanced statistical analysis. Prior experience in running neuromodulation studies including TMS and TUS is essential. You will be
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methodological and biological factors—such as the choice of substitution models, site saturation, and the role of selection, mutation, and recombination—that shape evolutionary rate estimates. A key goal is to