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methodological focus will be the precise determination of the number of confined water molecules, addressed through two parallel strategies: connecting the channel to a fixed-pressure reservoir, and the
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infer excitation conditions and quantify the impact of fast, tenuous shocks on ionized line emission. In parallel, high-resolution 3D MHD simulations of fast shocks interacting with dense interstellar
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functions such as memory and object recognition, as well as consciousness and mental states. This research has several distinctive features: it employs a parallel approach involving human and non-human
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computational perspective, this requires solving billions of systems of ordinary differential equations in parallel on adaptively refined meshes, while performing interpolation and tensor operations
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lake and river water levels. In parallel, socio-environmental signals on water-related extremes and pressures will be extracted using natural language processing and text-mining techniques, drawing
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a semi-industrial facility. In parallel, this PhD research will focus on investigating and optimising the process for removing arsenic from effluent, including through flocculation. Consequently
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test and compare the predictions of this new configuration against existing theories (which model these structures in parallel) using synthetic case studies. These numerical tests will aim to clearly
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enthusiastic about computational imaging and have experience in solving inverse problems. You enjoy scientific programming and thrive in collaborative, international environments, while also being able
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molecular programming, microfluidics, and engineering to design sophisticated algorithms for exploring and manipulating information encoded in DNA-based graphs. The position is fully funded by a
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) development of multi-physics models in both numerical simulations and analytical calculations, (iii) data analysis by programming, e.g. python and matlab, (iv) help and guide of Ph.D students in the team