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We are seeking a motivated and Talented experimentalist for a full-time Research Assistant in Quantum Thermodynamics within Professor Ares’ research group at the Department of Engineering Science
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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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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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radiation technology. Prior experience on spin-resolved ARPES or previous experience in setting up and maintain the operation of ARPES spectrometers will be an advantage. Candidates are expected