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mitochondrial behaviour. This is one of two PhD positions in “MitoPhyto” hosted at the Department of Mathematics, where this focusses on mathematics and modelling and the other is more focused on experimental
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development of new computational and mathematical models to quantify and predict infectious disease risk, particularly for identifying high risk individuals and groups. The PDRA will translate conceptual
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Your Job: This PhD project bridges between classical analytical methods and modern AI based techniques to analyse spike train recordings to advance our understanding of neural population coding
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more about our benefits and what it is like to work at SLU at https://www.slu.se/en/about-slu/work-at-slu/ Development of statistical methods for estimating plant population size and change Mathematical
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experimental and modelling approaches to explore mitochondrial behaviour. This is one of two PhD positions in “MitoPhyto” hosted at the Department of Mathematics, where this one has a biological focus and the
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on studying the principles of neural computation through recurrent neural networks, dynamical systems theory, and machine learning. - Develop mathematical and computational models of neural networks - Analyze
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for estimating plant population size and change Mathematical statistics Description: We are looking for a dedicated and goal-oriented PhD student who wants to contribute to the development of methods
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resilience. This task will involve integrating demographic models (e.g., structured population like matrix population models and/or integral projection models) with community stability analyses using, among
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Your Job: This PhD project aims at relating precisely timed spike constellations across subsets of neurons to low-dimensional manifolds of high-dimensional space of population neuronal firing rates
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). The main aim of this PhD project is to develop mathematical models relevant for processes at the anode of aluminium electrolysis cells, with emphasis on evolution of bubbles, including the so-called “anode