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complexity science, mathematical modelling in evolution, ecology and plant biology, along with transferable skills, including interdisciplinary communication and collaboration. You will also be offered
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environmental and life sciences challenges. Courses will cover topics such as complexity science, mathematical modelling in evolution, ecology and plant biology, along with transferable skills, including
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aluminium. The candidate will investigate various methods for symbolic regression, aiming to extract symbolic information, like mathematical functions or programs from a network trained for material modelling
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and accepted to the PhD program at Stockholm University. Project description Project title: “Deep learning modeling of spatial biology data for expression profile-based drug repurposing”. A new exciting
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Analysing biofilm structure and microbial communities Additionally, you will develop a mathematical model that includes both adsorption and biodegradation mechanisms. This model will be calibrated using pilot
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consist of the following: Mathematical analysis of ecological and eco-evolutionary models, involving pencil-and-paper calculations; Computer simulations of more complex models which do not easily lend
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of quick clays. A novel combination of miniaturised thermal-hydro-mechanical experiments and particle level modelling will be pursued to unravel the unique mechanisms that make quick clays so hazardous and
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the right one for you! This is a fully funded PhD position to develop micromechanical models of high-pressure die-cast aluminium, a unique opportunity for a motivated individual to work in a collaborative
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aims to build predictive and physical binding models of protein – DNA interactions using high-throughput and quantitative biochemical binding data across hundreds of thousands of sequence variants
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We are offering a PhD student position in machine learning (ML) theory, focusing on new methods for training models with a limited amount of data. The student will be a part of a new NEST initiative