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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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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
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Health, Geography, Global Affairs, or a related field, possess sufficient specialist knowledge in the discipline to work within established research programmes, experience writing computer code in Stata