37 phd-mathematical-modelling-ecological-modelling Postdoctoral positions at KINGS COLLEGE LONDON
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-based workshops; and System Dynamics Modelling, to understand how to maximise the contribution of Nature Based Solutions to climate change adaptation in the UK through multifunctional landscapes in
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this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD qualified in relevant subject area* Experience developing deep learning segmentation models
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and experience: Essential criteria PhD in bioinformatics, computational biology, or a related discipline * Extensive experience and expertise in analysing/ training models on biological or chemical
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structural development over time at the group, sub-group, and individual level (e.g., using normative modelling and clustering approaches to parse heterogeneity). The candidates will further have the
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About us The Green Laboratory investigates tissue morphogenesis and the action of morphogens. We use animal models to investigate the physical morphogenesis of tissues. It is part of the vibrant and
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of the microbiome in olfaction using mouse models. The selected applicant will join the vibrant and friendly Tucker lab and work as part of a team interacting with the group of Prof Mike Curtis. The postdoc will
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About us The Faculty of Natural, Mathematical & Engineering Sciences (NMES) comprises Chemistry, Engineering, Informatics, Mathematics, and Physics – all departments highly rated in research
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is led by Professor Mauro Giacca and comprises over 65 clinical and non-clinical academic groups, hosting 400 personnel and 110 PhD students. Our community of world-renowned researchers and educators
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for more information. About you To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD degree in Engineering, Computer
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of background knowledge; implicit knowledge is derived by performing reasoning over event graphs; and the comprehension model is developed with built-in interpretability and robustness against adversarial attacks