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position is embedded in a vibrant research environment that includes several PhD students and postdoctoral researchers. The project is a close collaboration between the Computer Vision Group at Chalmers
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combine large-scale data, computational methods, and clearly articulated social-science theories to improve our understanding of society. Recent advances in machine learning, natural language processing
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physics, applied mathematics, machine learning, bioinformatics, biophysics, spectroscopy, image processing, ecological modeling, molecular biology, plant physiology, marine biology or an interest in gaining
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combine large-scale data, computational methods, and clearly articulated social-science theories to improve our understanding of society. Recent advances in machine learning, natural language processing
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at the interface using computer simulations. At the beginning simulations will be used to model polymeric particles, such as microgels. With these simulations we will study how the individual particle
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fluids, flow-induced pattern formation in both simple and complex flows (e.g. flow instabilities, product defects), multiscale analysis, and the application of machine learning techniques. About the
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description The postdoctoral project is focused on development and the exploitation of machine learning tools to accelerate the analysis of microtomography data at the MAXIV synchrotron facility. MAXIV
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computational costs by orders of magnitude and enabling breakthroughs in drug design and materials science. The position bridges machine learning and molecular science, with opportunities for collaboration
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of mathematical areas. The position will be placed at the Department of Computer Vision and Machine Learning (CVML) at the Mathematics Centre (https://maths.lu.se/). Mathematics Centre is a department
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postdoctoral position in data analysis, where you will apply machine learning techniques to understand how resistance genes spread and to help detect infections caused by resistant bacteria. The position is part