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Field
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. Qualifications: You should have (or be close to achieving) a PhD degree. Background within computational methods for inverse problems, ideally tomography. Experience with development of numerical implementations
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of novel strategies for neuronal analysis in health and disease and optimizing novel methods. The project is funded by My Name’5 Doddie Foundation, as part of their Catalyst Awards. Using iPSC-neurons, our
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Do you have experience with modelling structures subjected to dynamic loading? Are you interested in data-driven methods for modelling applied loading? Are you eager to share your knowledge within
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and laboratory-based methods to investigate the long-term frequency and magnitude of historic and prehistoric earthquakes and tsunamis at the Cascadia, Alaska, and Chile subduction zones. The data
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diversity of methods and data available to the discipline. We are further developing our core undergraduate programmes and will be recruiting world leading staff accordingly to ensure these programmes
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, or similar disciplines Graduate students expecting to receive their PhD within six months can also apply Experience in the advanced analysis of genetic or proteomic data Interest in learning methods
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bases and instruments in terms of their efficiency and incidence Applied game-theoretic modelling based on 1) and on numerical estimates of the benefits that potential donor countries derive from
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provision of user-tailored climate services including products related to climate modeling. The successful candidate will have experience in two or more of the following areas: numerical climate modeling
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of the stock structure of many fish populations in the Baltic Sea is limited. For numerous species, we lack detailed knowledge about changes and spatial variation in migration patterns, reproduction, size and
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critical role in advancing computational materials science by developing and applying first-principles and machine learning methods, with a focus on interatomic potential development and large-scale