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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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• Uncertainty quantification around LLMs • Constrained optimal experimental design (active learning) • Combining models and combining data / Realistic simulation of clinical trials • Developing
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will have three responsibilities: - (1) studies of composite materials for a beam-facing RF shield. (2) contributions to the operation and exploitation of the Timepix4 testbeam. (3) simulation work
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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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found in Inertial Confinement Fusion (ICF) implosions transport of charged particles is a challenging problem that is difficult to simulate as well as diagnose in experiments. For example, particle
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objects such as neutron stars and black holes. Strong computational experience and proficiency in simulations is highly preferred. The post-holder may be expected to help in the supervision of DPhil and
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developing mathematical algorithms and simulations in MATLAB, in particular with Semidefinite Programming and Sum of Squares and of the analysis and design of feedback control systems using these approaches
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trapping or fluorescence microscopy to study DNA replication; • develop and employ simulations and data analysis routines to analyze your data; • develop an interdisciplinary skillset by
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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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necessary for the benefit of the project; • employ simulations and data analysis routines to analyze your data; • help to establish a scientifically outstanding and warmly communicative