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Field
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probabilistic ensemble techniques to improve uncertainty representation in climate simulations. Apply and validate Monte Carlo methods (e.g., importance sampling and other rare-event estimation methods
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Computational Biology, Bioinformatics, or a related field (e.g. statistics, computer science, or quantitative biology). Experience in the application and development of computational methods/tools or machine
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areas (i) Non-adiabatic chemical dynamics, (ii) Physics of charge transport in the solid state, (iii) QM/MM methods, (iv) Atomistic classical simulations of macromolecules (v) Biophysics. You can write
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to methods and principles aimed at understanding and modelling the mechanics of deformable bodies. Solid mechanics is a core discipline in mechanical engineering and is of fundamental importance to many other
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with various methods that can incorporate domain-based constraints and other types of domain knowledge into machine learning and applying these techniques to problems in computational creativity
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of their career developing state-of-the-art statistical and mathematical methods to analyze epidemic data, with the aim to increase our understanding of how pathogens spread in populations, assess the impact of
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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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| Electrical and Computer Engineering This position researches theoretical and experimental methods for the detection of counterfeit integrated circuits assists with the development of grant writing and
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polymer physics. The successful candidate will develop strategies to design, synthesize, and characterize the properties of soft materials using advanced microscopy techniques and related methods
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(e.g. in automotive applications) using, for example, vibration and acoustic signals. Research questions include method development for fault detection and isolation, damage estimation systems, including