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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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in Cambridge. The mission statement of the group is "developing statistical methods to use genetic variation to answer clinically important questions about disease aetiology and prevention". The three
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to supervision of MSc and PhD students, and participate in departmental seminars and collaborative meetings. You will also be encouraged to attend and present at national and international conferences, with
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digital topography, supplemented with fieldwork in selected regions. The production of high-resolution digital topographic datasets through field-based, aerial, or satellite methods, forms an important
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to supervision of MSc and PhD students, and participate in departmental seminars and collaborative meetings. You will also be encouraged to attend and present at national and international conferences, with
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mathematical and computational techniques, it is essential to have experience in mathematical modelling / dynamical systems theory / numerical methods / coding. An ideal candidate would have a PhD, or
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will be offered a fixed 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 PhD in Law/Socio
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Learning, Algorithms, Noise Handling (Error Correction/Mitigation), and Verification. These roles are part of the Quantum Software Lab (QSL, link: https://www.quantumsoftwarelab.com ), in collaboration with
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batteries Conduct preliminary sustainability analyses to evaluate the environmental consequences of the chosen materials and fabrication methods Evaluate the long-term ecological responsibility
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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