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on the training strategies. In this project, we will investigate Bayesian methods to train deterministic SNNs (with deterministic activation functions) or probabilistic SNNs. Bayesian deep learning methods have
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bodies. Applicants will possess a relevant PhD (Physics, Optics, Photonics, Optical Engineering or nearing completion) or possess an equivalent qualification/experience in a related field of study and be
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-leading physics capabilities and enable time-dependent, non-LTE radiative transfer magnetohydrodynamic (MHD) simulations. The framework will be released as open-source software, with a strong emphasis on
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of new contexts and methods of education in late antiquity. The postholder will also be expected to co-organise and take part in project-related events and activities. About you Applicants will possess a
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seminars etc Supervise students on research related work and provide guidance to PhD students where appropriate to the discipline Contribute to developing new models, techniques and methods Undertake
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term contract for 3 years. About you To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria 1. PhD in Law/Socio-legal Studies
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, calcium imaging, optogenetics and/or behavioural methods. The project is part of a broader research programme designed to use cross-species research to uncover mechanisms for memory in both health and
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on transplant using multimodal medical data. You will be responsible for literature review, data cleaning, model development and implementation. You should possess a relevant PhD (or near completion) in
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. Traditional methods for coating and stabilizing LFP cathodes often face limitations in durability and electrochemical efficiency. This research aims to overcome these challenges by applying innovative coating
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analysis of PDEs (with deterministic and/or stochastic methods), Gaussian Random Fields, mathematical foundations of deep learning, functional analysis and measure theory. You can find more information about