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materials and technologies. Using advanced computational modeling and machine learning, we seek to elucidate the mechanisms governing the self-assembly of lignin in different solvents and the formation
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, volumetric data analysis, optimization methods, statistical modeling, or machine learning for scientific applications. Prior experience with cryo-EM software frameworks or structural biology data is considered
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these plants. The post-doc is expected to build upon existing in-house tools and, where applicable, enhance them by means of AI (machine learning) and data-driven methods. These models are aimed to support
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) training personalized computational models in new contexts, and (iii) studying in-silico clinical intervention strategies. The postdoctoral fellow will have the opportunity to: Learn about computational
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, volumetric data analysis, optimization methods, statistical modeling, or machine learning for scientific applications. Prior experience with cryo-EM software frameworks or structural biology data is considered
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Are you interested in developing machine learning algorithms that provably help us make better decisions? Join us as a post-doc in the Division of Data Science and AI, Department of Computer Science
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mathematical modelling and machine learning both using simulated and real data. Work duties The main duties involved in a post-doctoral position is to conduct research. Teaching may also be included, but up
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–classical algorithms or optimization methods Background in uncertainty quantification, reduced-order modeling, or machine learning Experience collaborating in interdisciplinary research teams A doctoral
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experience with 3D image processing, volumetric data analysis, optimization methods, statistical modeling, or machine learning for scientific applications. Prior experience with cryo-EM software frameworks
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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